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This paper presents a solution method to suppress reflections from the walls in an anechoic room using active control, in which the control coefficients are obtained with an efficient algorithm. One of the main challenges in suppressing the reflections, is the estimation of the reflected sound field, which is a non-measurable quantity. The reflected sound field is computed using the Kirchhoff-Helmholtz integral with a set of microphones on a circle. The effectiveness of the method is shown on an experimental setup. The experimental setup is a small-scale version of an acoustic anechoic chamber. An anechoic chamber, with larger dimensions and higher frequencies, will result in a system with a relatively large number of sources and sensors. It is computationally expensive to find a set of control filters for larger-scale systems. The conjugate gradient algorithm using block-circulant preconditioning is an efficient method to solve for the optimal set of control filters. The preconditioned conjugate gradient algorithm is used together with the Kirchhoff-Helmholtz integral. Real-time measurements show that the reflections are effectively suppressed, expressed in terms of the reverberation time. This results in a small-scale active anechoic chamber. • The reflected sound field has been suppressed in real-time using active noise control. • A preconditioned conjugate gradient algorithm has been modified for practical implementation. • The reflected sound field is computed in real-time with the Kirchhoff-Helmholtz integral. • The reverberation time has been reduced using a real-time active noise control system. [ABSTRACT FROM AUTHOR]

[Display omitted] • Implementation of active noise control (ANC) is tested in a full-scale plenum window. • A comparison is made for single, and decentralized dual-channel ANC configurations. • Dual-channel ANC can achieve 6 dB local attenuation below 500 Hz or 5.4 dB below 800 Hz. • ANC applied in the plenum window proved effective against other common urban noises. • The developed ANC system remains robust even with mechanical ventilation operating. Plenum windows, also known as ventilation windows, allow for natural ventilation in living spaces while providing noise reduction to improve the health and living comfort of occupants, especially in noise-polluted and tropical/sub-tropical cities. However, while plenum windows can provide acceptable levels of natural ventilation, the passive noise performance of plenum windows when fully opened is still lacking as compared to the conventional closed windows- especially in the low frequencies experimentally. Active noise control (ANC) has shown good performance in several applications for low-frequency control. Thus, the application of ANC using a single-channel and decentralized dual-channel ANC implementation, informed by prior simulation studies is developed and field tested for a plenum window in a domestic setting built to reproduce the environment of a high-rise apartment. The experiments show that the average global attenuation benefit in the apartment room due to a single-channel ANC is 2.9 dB in the 100 Hz – 500 Hz range while the decentralized dual-channel ANC provides up to an average of 4.8 dB reduction in the 100 Hz – 500 Hz range or an average reduction of 3.8 dB in the 100 Hz – 800 Hz range. The decentralized dual-channel ANC is also tested under different noise types and is effective in low-frequency control. Furthermore, the dual-channel ANC remains robust even with an additional mechanical ventilation system operating inside the plenum window, improving the natural ventilation. [ABSTRACT FROM AUTHOR]

• Factors affecting the performance of virtual feedback control system are analyzed. • Reducing delay or increasing physical microphones improves noise reduction. • Experiments in an electric car running at 50 km/h are conducted. • A binaural noise reduction of 3.4 dBA is obtained inside an electric car cabin. This paper analyzes the factors that affect the noise reduction performance of feedback control based on remote microphone technique (RMT) and how these factors can be exploited to improve the control performance. First, simulations were conducted to compare the noise reduction performance of employing feedback control directly at the virtual microphone (located at the ear position) and on the physical microphone (located on the headrest), as well as the RMT-based feedback control system. Then the impact of the delay of the virtual secondary path and the coherence between physical and virtual signals on the noise reduction performance of the RMT-based feedback control system was analyzed. It is found that the noise reduction performance can be improved by reducing the delay of the virtual secondary path or increasing the number of physical microphones. Finally, experiments of a dual-channel control system conducted inside an electric car cabin demonstrate that the feedback control strategy based on RMT achieves a binaural noise reduction of 3.4 dBA when employing 4 physical microphones to estimate sound pressure at the ear positions. This approach achieves similar performance but is more cost-effective than a feedforward system using multiple reference sensors. [ABSTRACT FROM AUTHOR]

When implementing active noise control systems on signal processing hardware, the time delay introduced by electronic components (especially components requiring additional lowpass filters or introducing fixed-sample-size delays) may adversely affect the noise control performance. One common approach to reducing this delay is to use a high sampling rate, but this increases the computation significantly when implementing the ANC filters in real time. In the current work, a polyphase-structure-based filter design method is developed for active noise control systems that can reduce the computation load for real-time filter implementation but do not introduce an additional time delay. Although the computation reduction capability of a polyphase filter structure is well known for multi-rate systems, the traditional use of such multi-rate systems requires additional anti-aliasing and reconstruction filters which introduces an additional time delay. Thus, in delay-sensitive applications, such as active noise control, this method was previously applied only on the filter adaption phase, instead of directly on the real-time filtering process. In this article, a filter decomposition method using the minimum-phase technique is proposed to decompose an ANC filter into two multiplicative causal filters both of which have lowpass frequency response shapes at high frequencies such that the polyphase structure can be applied directly to the two multiplicative causal control filters without introducing additional anti-aliasing and reconstruction filters. Results show that, compared with various traditional low sampling rate implementations, the proposed method can significantly improve the noise control performance. Compared with the non-polyphase high-sampling rate method, the real-time computations that increase with the sampling rate are improved from quadratically to linearly. • A filter implementation structure designed for delay-sensitive applications. • The real-time computations that increase with the sampling rate are reduced from quadratic to linear. • Significant noise control performance enhancement compared with traditional methods. [ABSTRACT FROM AUTHOR]

• Proposing the reference signal selection method based on the genetic algorithm (GA). • Proposing a multi-channel VSS-TF-HANC algorithm for active control of road noise. • The proposed algorithm performs excellent noise reduction performance and low computational complexity. • The proposed algorithm achieves good noise reduction performance under complex driving conditions. • The proposed algorithm is able to achieve noise reduction at multiple noise reduction locations. Multi-channel Active Road Noise Control (ARNC) systems require numerous adaptive filters to reduce noise at multiple positions inside the vehicle. However, road noise conditions are more complex, and the correlation between the reference signals and the target noise is often poor. When the driving conditions become slightly complex, the correlation between the reference signal and the target noise is often poor. As a result, traditional road noise control algorithms applied to multi-channel ARNC systems often suffer from high computational cost and poor noise reduction performance in non-steady-state and high-speed driving conditions. To address this issue, a reference signal selection method based on the genetic algorithm (GA) is proposed to obtain a reference signals combination with stronger coherence. On this basis, we introduce the time–frequency domain structure into the forward-feedback hybrid algorithm and a multi-channel time–frequency domain hybrid algorithm with a novel variable step size method (VSS-TF-HANC) is proposed in this paper. The feedforward part adopts a time–frequency domain structure and introduces a novel variable step-size strategy to reduce computational complexity and improve noise reduction performance. The feedback part adopts a control system based on the Internal Model Control (IMC) architecture to attenuate the interior noise components that have a strong response but poor correlation with the reference signals. Simulation results demonstrate that the proposed algorithm achieves excellent control results under complex driving conditions, with significantly better noise reduction performance compared to the control algorithms that solely employ the feedforward structure, while also exhibiting low computational cost. [ABSTRACT FROM AUTHOR]

To reduce the computational burden of the bilinear FLANN (BFLANN) filter for active noise control (ANC), an M-max partial update leaky bilinear filtered-error least mean square (MmLBFE-LMS) algorithm is proposed in this paper. Unlike the algorithm based on filtered-reference technique in BFLANN-based ANC system, the proposed MmLBFE-LMS algorithm uses the filtered-error method and data-dependence partial update strategy to reduce computational complexity, and employs a leaky technique to mitigate the instability problem as in bilinear filters. The simulation results and computational complexity analysis indicate that the proposed algorithm can significantly reduce the computational burden of the BFLANN-based ANC system without suffering from noise-canceling performance degradation. [ABSTRACT FROM AUTHOR]

The computational efficiency of the filtered-x least mean square-based narrowband active noise control (FX-NANC) system is heavily dependent on the number of targeted frequencies and the length of the estimated secondary path, so that its performance may be limited in the case of multi-frequency noise. In order to address this limitation, filtered-error least mean square (FELMS) algorithm is first considered in narrowband active noise control (NANC) system in this paper. Compared to the FX-NANC system, the FELMS-based NANC (FE-NANC) system requires only one error signal filtering block regardless of the number of targeted frequencies. As the increase of the number of targeted frequencies and/or the length of the estimated secondary path, the FE-NANC becomes much more cost-saving. The closed-form convergence analysis of mean and mean-square of the FE-NANC system for discrete Fourier coefficients (DFC) and error signal are derived along with the stability condition on step size. Numerical simulations comparing FE-NANC with other NANC systems and the real-time implementations of FE-NANC demonstrate the effectiveness of FE-NANC system. Furthermore, we show that the numerical results of FE-NANC system agree with theoretical predictions. [ABSTRACT FROM AUTHOR]

The algorithms for online secondary path modeling, with the injection of auxiliary noise, have always been applied to active noise control (ANC) systems to deal with the problem of when the secondary path is time-varying. The applications of ANC in vehicles for active sound quality control may pose new challenges for the current online secondary path modeling algorithms due to the disturbance noise signal from unconcerned frequencies. Therefore, this paper presents a framework of online secondary path modeling for active sound quality control systems. On the basis of current algorithms, an adaptive step size least mean square (ASS-LMS) algorithm of the secondary path modeling with interference signals is proposed. The ASS-LMS algorithm improves the stability of iteration without reducing convergence speed. Furthermore, a modified strategy for scheduling the auxiliary noise power is also proposed. The proposed modification reduces the degradation of the sound quality control performance caused by auxiliary noise. Simulations results are provided to verify the effectiveness of the algorithms proposed in this paper. [ABSTRACT FROM AUTHOR]

The nonlinearities of active control systems are the main factors that deteriorate noise-reduction performance. To improve the performance of a control system with a nonlinear secondary path, a filtered-x least mean square algorithm using reweighted bilinear filters is proposed in this paper and a generalized filter to model different nonlinear secondary paths is explored. Within the controller of an adaptive feedforward control system, the proposed algorithm uses trigonometric expansions to achieve high-order nonlinearities and combines the cross terms between the controller output, sine and cosine functions of the input with the reference signal. As a result, satisfactory control performance can be achieved with a shorter memory length of the controller compared to certain control algorithms. It is also found that the introduction of a reweighting factor in the weight-updating process can effectively reduce the interference produced by the small coefficients of the control filter and accelerate the convergence rate. The computational complexity of the proposed algorithm is analyzed and its control performance is verified through simulation experiments with different nonlinear secondary paths and input noises. Simulation results show that the proposed algorithm outperforms four other widely accepted algorithms in terms of convergence rate and residual error. [ABSTRACT FROM AUTHOR]

• A generalized fractional low-order moment (FLOM)-based adaptive algorithm. • Time varying step-size using convex-combined step-size (CCSS) approach. • Application demonstrated for active noise control (ANC) of impulsive sources. • Fast convergence speed as well as good steady-state performance. This paper develops a generalized fractional low-order moment-based adaptive filtering algorithm well suited for active noise control (ANC) of noise sources exhibiting peaky characteristics. In a previous algorithm, the impulsive nature of the noise sources has been addressed by employing a normalized step-size and the fractional power of the error and reference signals. In this paper, we employ a convex combination approach to develop a variable step-size (VSS) strategy. Thanks to the VSS in the proposed algorithm, the ANC system achieves a fast convergence speed as well as an improved steady-state noise reduction performance. Extensive simulations have been carried out for various scenarios, which show that the proposed algorithm is robust against the impulsiveness of the noise source as well as for a possible non-stationarity in the acoustic environment. [ABSTRACT FROM AUTHOR]

This research focuses on the use of an open window with an active noise control (ANC) system and a splitter silencer to improve the attenuation level of broadband noise. We previously introduced a similar idea with a splitter silencer and a loudspeaker inside a duct. However, it is challenging to achieve noise reduction with a splitter silencer in a short duct. In our previous research, we achieved noise reduction at an open window with an array of ANC units, in which a reference microphone with a loudspeaker is collocated. However, this system had limited high-frequency noise reduction due to the distance between each loudspeaker. Here, we improved noise reduction by integrating a collocated ANC system and a splitter silencer, which has an open ratio of 50%. Each unit has a reference microphone at the front and a loudspeaker at the back, which generate anti-noise. Four units are combined in an array with a splitter silencer. In an experiment, we implemented two splitter silencers in an eight-channel ANC system at an open window (24 × 48 × 12 cm). The results show that the splitter silencers attenuated high-frequency noise above 2 kHz. Moreover, the ANC system achieved an attenuation of 2 to 10 dB for noise in the range of 200 Hz to 2 kHz. Overall, we were able to achieve a total attenuation of 2 to 17 dB above 200 Hz. [ABSTRACT FROM AUTHOR]

Active noise control is a well-known technology for the attenuation of disturbing sound or vibration. Feedforward control is efficiently employed, especially if stochastic disturbances are to be suppressed. If the unwanted noise is generated by multiples sources, multiple reference sensors are also used. The behavior of multiple reference feedforward systems has been investigated in the last decades, with special emphasis on the speed of convergence. It has been proven that reference preprocessing can significantly speed up such systems. However, less attention has been paid to the attainable suppression. This paper provides the analysis of multiple reference systems with respect to the steady state, and an upper bound for suppression is also expressed. Besides, the single reference case, and the influence of preprocessing is discussed. The theoretical results are supported by simulation and experimental examples. • Active noise control is used for the attenuation of multiple noise sources. • The performance is limited by the coupling of the noise capturing microphones. • The arrangement is investigated and an upper bound for suppression is provided. [ABSTRACT FROM AUTHOR]

This paper investigates the feasibility of increasing the noise reduction performance of active noise control systems on ground by introducing a finite size reflecting surface vertical to the ground. By using the image source method and the disk scattering model, the sound radiation power of an active noise control system on ground with an additional finite size semicircular rigid disk vertical to the ground is studied. It is found that the noise reduction of the system can be increased significantly with the infinitely large reflecting surface when the primary and secondary source distance is less than half of the wavelength at the frequency of interest, and the finite size disk can further increase the noise reduction performance at certain bandwidth by up to 2.3 dB. The mechanisms for the performance increase are explored, and the experimental results are presented to validate the analytical and simulation results. [ABSTRACT FROM AUTHOR]

Active noise control (ANC) is a technology which lowers the noise level by using the principle of destructive interference of sound wave. Performance of active noise control, generally, is highly related to the number of reference transducers, secondary speakers, and error microphones. However, the more number of transducers, microphones and speakers are used for improving ANC performance, the higher computational requirements of such an ANC algorithm would be. Currently, limited computational efficiency of conventional DSP systems hinders the possible maximum noise reduction performance of ANC. In the previous research, for figuring out the limited ANC performance issues due to a lack of computational efficiency, graphics processing units (GPU), which possesses significant parallel computational efficiency, is utilized for ANC algorithms. However, ANC algorithms with GPU computations in the previous researches have limitations on the fact that they are designed in frequency domain structure due to a block data transfer between central processing units (CPU) and GPU, which suffers from a block delay in control signals. Therefore, throughout this research, we proposed a CPU-GPU architecture for ANC algorithms, which does not suffer from the problems of frequency domain algorithms and take advantage of GPU computation. Also, we suggested important factors needed to be concerned when an ANC algorithm based on CPU-GPU architecture is being developed. The feasibility of the proposed CPU-GPU architecture for ANC algorithms is shown with an example of implementing the proposed CPU-GPU architecture on multichannel delayless subband ANC algorithm. [ABSTRACT FROM AUTHOR]

Abstract This article presents a hybrid acoustic technique applied to an acoustic shutter. It uses active noise control (ANC) at frequencies below 1000 Hz and acoustic foam, glued at the shutter walls, to attenuate frequencies above 1000 Hz. The use of the active noise control applied to acoustic shutters to increase the performance of noise attenuation in low frequencies. The control system was the Feedforward Filtered-x Least Mean Square (FxLMS) scheme and the influence of the actuator speaker position. It was implemented a low-cost active noise control using ARDUINO DUE. At low frequencies, without active noise control, the average insertion loss of the acoustic shutter is approximately 7 dB. Up to cutoff frequency (565 Hz) of the acoustic shutter, the highest attenuation due to active noise control was approximately 14 dB in 125 Hz discrete frequency and 17 dB in 400 Hz 1/3 octave band. The results between 500 and 1000 Hz were interesting since the active noise control was not expected to be efficient above the cutoff frequency of the acoustic chamber. The highest attenuation was 17.5 dB at the frequency of 710 Hz. From 100 to 8000 Hz an average attenuation of 13 dB (1/3 octave bands) was observed using the semi-active apparatus presented in this article. [ABSTRACT FROM AUTHOR]

Highlights • Experimental validation of global active noise control using Modal FxLMS algorithm is carried out. • Experimental study on a rectangular box vibro-acoustic cavity under the presence of acoustic and structural distrubances using one and two control loudspeakers is presented. • Modal secondary paths are experimentally identified. • Modal control at a cavity-controlled and a panel-controlled resonance is presented. • Modal control with different choices of modes under control is carried out. Abstract The Modal FxLMS algorithm is recently proposed for reduction of global level of noise in vibro-acoustic cavities. The algorithm minimizes acoustic potential energy expressed in modal domain which allows a choice of acoustic modes whose modal amplitudes are desired to be minimized. The working of the algorithm and its effectiveness has been demonstrated previously through a numerical study and an experimental study is required to test the effectiveness of the algorithm in practice. To meet this objective this paper presents an experimental study of this algorithm for global active noise control in a rectangular box cavity. The algorithm utilizes modal filtered reference signals and modal amplitudes of the selected acoustic modes of the cavity. To identify modal filtered reference signals, modal secondary paths are utilized. In the present study, modal secondary paths are identified using experimentally identified physical secondary paths and acoustic mode shapes. Modal amplitudes of the acoustic modes are identified on the basis of acoustic pressure measurements from eight microphones suitably placed throughout the cavity. The performance of the algorithm is studied under the presence of acoustic and structural disturbances using one or two control loudspeakers. The active control is carried out at harmonic frequencies coinciding with cavity-controlled resonances and panel-controlled resonances. It is found from the experimental results that the Modal FxLMS algorithm is successful in reducing modal amplitudes of the selected acoustic modes. When all the significantly contributing acoustic modes are chosen, a reduction in global level of noise is observed at cavity as well as panel controlled resonances. [ABSTRACT FROM AUTHOR]

Highlights • An active structural noise control method based on PZT material and fuzzy algorithm is presented. • A simplified vehicle cavity model with a smart plate and PZT transducers is constructed. • A fuzzy controller is designed and improved by adjusting some quantization factors. • A PZT-based system is established for active structural noise control of vehicle interior noise. • Experimental results show an effectiveness of the presented active structural noise control method. Abstract An active control approach for interior noise of vehicle based on the piezoelectric ceramic materials and fuzzy control algorithm is presented in this paper. According to the electromechanical coupling characteristics and the positive/inverse mechanism of a piezoelectric material, a theoretical model of piezoelectric ceramic plate with a sandwich structure is deduced by using impedance analysis method. The size of a piezoelectric ceramic transducer (or actuator) and its sticking position on the plate frame are determined. The structural modes and dynamic responses of a vehicle cavity model are calculated by finite element analysis for selecting optimal positions of actuator on the front wall. Furthermore, a fuzzy controller is designed for active vibration control. The fuzzy algorithm is improved by adjusting quantization factors, such as the deviation and its changing rate. Following the derived piezoelectric equations and the improved fuzzy algorithm, an active structural acoustic control (ASAC) system is developed and a functional prototype is set up by using the dSPACE platform. Experimental results show that the developed ASAC system can significantly reduce not only the vibrations of the front wall, but also the interior noises of the cavity. This implies that the proposed vibration-based ASAC method is effective and feasible, which might be a potential approach for interior noise control of vehicles. [ABSTRACT FROM AUTHOR]

Abstract The presence of uncorrelated disturbances at the error sensor of an active noise control (ANC) system has become very common with increase in the use of industrial machinery such as rotating machines, fans, vehicular motors, etc. The feed-forward ANC system employing filtered-x least mean squares (FXLMS) algorithm to solve this problem has not produced acceptable noise canceling performance. We propose a new cascading time-frequency domain FXLMS algorithm for active control of uncorrelated disturbances in a feed-forward ANC system. In the proposed method, the error signal of the ANC system containing the uncorrelated disturbances is decomposed into various band-limited parts using the discrete wavelet transform (DWT). Dividing the uncorrelated disturbance into various parts enables independent analysis of each part resulting in improved accuracy of error modeling. As a result of this multi-resolution analysis of the error signal, a superior noise canceling performance is achieved. Numerical simulations validate that the proposed algorithm outperforms its counterparts in terms of noise canceling performance and achieves faster adaptive filter convergence as well. [ABSTRACT FROM AUTHOR]

Abstract There are well-established measurement standards for the rating of impact noise reduction provided by floor coverings in relation to structurally transmitted impact noise, e.g. BS EN ISO 10140-3 and ASTM E492 are widely used in Europe and North America Respectively. Standardisation for "in-room" impact noise transmitted by an airborne path is however less well established. At the current time the standard used for rating the "in-room" impact sound reduction is BS EN 16205:2013 which focuses primarily on walking noise as a the impact source. This standard employs the same tapping machine used for impact improvement testing in BS EN ISO 10140-3 but has been found not to be ideal due to the mechanical noise it produces and because it is not fully representative of the walking loads that the standard primarily aims to address. There is currently no standard that deals with "in room" impact noise from falling objects which may be a greater concern than walking noise, for example in a healthcare or education setting. Thus, presented in the paper are the findings from a large measurement survey conducted to investigate the influence of impactor mass, hardness and velocity on measured "in room" impact noise reductions. Other measurands such as the reduction in impact force and floor acceleration are also considered. It is discussed in the paper how 'In-room' impact noise differs from transmitted impact noise and this is demonstrated by performing a transfer path analysis to separate out the impact noise contributions from a falling object and from the floor. The key finding of the study is that the whilst the impact noise reduction achieved by different floor coverings varies wildly for different impactor types the rank order of the floor coverings tested in terms of Impact noise reduction did not. Thus, the ideal test method may not be the one that simulates best the type of impacts a floor is likely to be subjected to, but rather, it ought to be the one that gives the biggest differences between similar floor coverings so as to highlight most clearly the differences between them. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a new hybrid narrowband active noise control (HNANC) system which effectively counters noise from multiple sources is proposed. Usually, active noise control (ANC) systems fail in the event of encountering uncorrelated noise, since such systems mostly are designed to operate when disturbances correlated to the reference signal are present. To deal with the multiple-noise scenario in an industrial environment, a new adaptive control strategy is introduced consisting of three subsystems: 1) a narrowband feedforward controller where we use filtered-x weighted accumulated LMS (FXWALMS) in combination with a new variable momentum factor scheme, 2) a feedback ANC system adapted by the FXLMS algorithm to specifically counter uncorrelated disturbances, and 3) the supporting adaptive filter that has a twofold objective, firstly, to provide appropriate error/reference signals to the noise cancelling adaptive filters and secondly, to provide the most accurate energy estimate of the constrained error signal for the variable momentum factor to improve the steady state performance of the feedforward controller. For improved adaptive filter convergence, we also reduce the number of reference signal filtering blocks in the feedforward NANC controller. A detailed mathematical analysis of the hybrid structure is performed to establish the basis for the proposed algorithm. Extensive simulations show that the proposed HNANC system gives an improved overall ANC performance over that of existing counterparts. [ABSTRACT FROM AUTHOR]

Abstract In this paper, strength of recently introduced nature inspired heuristic computing technique named fireworks algorithms (FWA) and its variants are exploited in the field of system identification based on active noise control (ANC) systems. Residual error based fitness function is constructed for ANC system and optimization of parameter is carried out with the help of fireworks, enhance fireworks and adaptive fireworks algorithms. The design scheme is applied to number of scenarios of ANC system for different primary and secondary paths. The designed methodology is evaluated for three different noise interferences based on sinusoidal and random signals. The scheme validated by means of accuracy and convergence operators through the results of statistics based on ample number of independent trails. The comparative study of results is also made for three variants of FWA to establish their worth in terms of precision, stability and complexity measures. [ABSTRACT FROM AUTHOR]

Highlights • Reduction of noise transmitted through a real device casing is investigated. • Vibrations of casing walls are controlled with an adaptive control system. • Its operation has been experimentally verified on an unmodified washing machine. • Noise reduction exceeded even 10 dB globally in the entire room space. Abstract An actively controlled thin barrier may provide better noise reduction results than common passive solutions. The performance of such active method has been confirmed by the authors using a dedicated noise-cancelling laboratory casing. Now, such approach is developed and applied to a real device casing, what is a significant step toward commercialisation of the active casing method. An adaptive FXLMS algorithm with practical modifications is proposed for the active control of the casing to provide noise reduction. A feed-forward structure is used, with a reference microphone located inside the real device. Additionally, an Internal Model Control system with reference signal estimation is also implemented for a comparison. The performance of the resulting control systems is experimentally verified for a real washing machine (an off-the-shelf product), using a loudspeaker placed inside the washing machine to provide reproducible noise. Obtained results are reported and discussed. [ABSTRACT FROM AUTHOR]

Abstract The active noise control (ANC) algorithms are widely applied in noise-canceling headphones. However, the disadvantage of conventional ANC algorithms is the high computational cost from high order finite-impulse-response filter, which also leads to slower convergence. Subband ANC algorithms, which are based on the subband adaptive filter, are used to reduce computational complexity and to increase convergence rate. Moreover, noise cancellation performance decreases at the higher frequency due to the decreasing control zone. In headphones based application, perceptual quality of noise attenuation and target audio signal are important factors, and ANC algorithm must be designed to account for the psychoacoustic parameters. In this paper, we propose a new noise reduction approach in order to solve some existing ANC headphones problems, especially high-frequency noise reduction and perceptual quality of the playback sound. The proposed algorithm is a new approach of integrated psychoacoustic subband ANC and psychoacoustic masking. Psychoacoustic subband ANC achieves lesser computational cost than conventional subband ANC by using the psychoacoustic model to attenuate only audible noise components during music playback in the headphones. Proposed new integrated system is efficient for broadband noise attenuation. Psychoacoustic ANC reduces noise in the most sensitive frequency range for human's hearing system, 0–4000 Hz, and masking operates in order to mask out residual and high-frequency noise. In additional, proposed noise reduction system reduces only audible noise components. The integrated ANC-masking system applied psychoacoustic analysis without producing artificial distortions to the music signal. Objective and subjective perceptual tests are evaluated for the proposed ANC-masking system with other subband ANC and masking algorithms. Results show the advantage of the proposed integrated system in the terms of the perceptual sound quality and high-frequency noise reduction. [ABSTRACT FROM AUTHOR]

Abstract Active noise control (ANC) is the most popular method for attenuating acoustic primary noise or disturbances by generating controllable secondary sources by which the output noise can be cancelled with the same amplitude but with opposite sign/sense. Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. The modelling requirement of the secondary path increases the complexity of the system implementation and decreases the control system performance. Recently several new ANC algorithms have been developed; in which there is no requirement for the modelling of the secondary path transfer function. In this regard, the aim of this paper is concerned about a narrowband feedforward ANC system in systems like air intake duct system and its novelty is to introduce all-pass filtered x LMS (APFxLMS) algorithm which do not require an estimation of the secondary path. Here first-order all pass filters with single parameter is used to improve the convergence of the LMS algorithm. The performance evaluation in terms of convergence speed of the proposed algorithm is validated with standard ANC without secondary path modelling. The results also show that the proposed method outperforms other LMS algorithm without secondary path modelling. The proposed narrowband LMS algorithm would benefit in the design of efficient feedforward ANC system that can realize noise control in air intake duct applications. [ABSTRACT FROM AUTHOR]

• Two virtual sensing methods are proposed for scattered sound control. • Adaptive algorithm is adapted so as to attenuate scattered sound in impulsive form. • The performance of two proposed methods is experimentally validated and compared. • Both methods can control the target scattered sound with limited sensor placement. Active control method is an important way to reduce the scattered radiation of 3D objects and render them acoustically invisible. Traditional active control requires the error sensor to be sufficiently close to the target area because the zone of quiet (ZoQ) is generated around the sensor; thus, the scattered noise cannot be eliminated at the remote position in situations wherein the microphone can only be placed near the scatterer. To solve this dilemma, this study proposed two methods of predicting and controlling the scattered sound, combined with adaptations of two commonly used virtual sensing (VS) methods: the auxiliary-filter-based virtual-sensing (AF-VS) and the remote microphone technique (RMT). Both methods are based on the correlation between signals to predict the scattered noise; therefore, ZoQ can be transferred to the non-near-field target position with fewer physical microphones. Further, the causal constraints need not be satisfied in the former method, which uses pre-trained auxiliary filters to implicitly estimate and control the scattered pressure at the target point. Whereas, the latter explicitly estimates the scattered component instead of the total sound pressure with the pre-modeled observation matrix, thereby avoiding the causality limitation of the RMT and reducing one estimation process. Experiments were conducted to suppress impulsive scattered sound using a dual-channel feedforward adaptive ANC system, and the attenuation performances of the two proposed methods were compared with those of the direct control of the desired noise with the optimal Wiener solution and the method without combining the VS. The results demonstrated the feasibility and effectiveness of the two active control methods for scattered sound using virtual sensors. Moreover, in the impulsive scattered sound control with a 300 Hz-1000 Hz carrier, the average noise reduction (NR) at the observation points reached approximately 18 dB, and a more stable and excellent performance was obtained using the latter method based on RMT. Therefore, this research provides a solution for the case of limited error sensor placement in scattered sound active control systems; and in addition, can be used to guide the choice of VS methods in scattered sound control applications. [ABSTRACT FROM AUTHOR]

The nonlinear adaptive exponential functional link artificial neural networks (E-FLANN) filter has been introduced to improve the noise reduction capability of the functional link artificial neural networks (FLANN) in nonlinear active noise control (NANC) system. It, however, suffers from a heavy computational burden at the nonlinear secondary path (NSP) and poor convergence performance in strong nonlinearity systems. To surmount these shortcomings, a computationally efficient generalized E-FLANN filter with the channel-reduced diagonal structure (GE-FLANN-CRD) for NANC system is developed in this paper. Based on introducing the suitable cross-terms and adaptive exponential factor into the trigonometric functional expansions, the nonlinear processing capability of the filter is enhanced in NANC. Also, by applying the filtered-error least mean square (FELMS) algorithm to the GE-FLANN-CRD, it substantially decreases the computational cost to update the exponential factor. Computer simulations demonstrate that the proposed filter-based the NANC system performs better than the FLANN, E-FLANN and Generalized FLANN (GFLANN) filters-based NANC system in the presence of strong nonlinearity. [ABSTRACT FROM AUTHOR]

Active noise control through open windows is a noise mitigation technique that preserves natural ventilation in dwellings. Designing a practical open window active noise control system requires the knowledge of the physical limits on the attenuation performance. Of the numerous variables to be optimised, it is the control source configuration (quantity and position) that ultimately defines the maximum attenuation attainable by an active noise control system. The physical limits are characterised here by systematically investigating the performance of different physical arrangements of control sources, using a two-dimension simulation model based on the finite-element method, which includes the diffraction effects of the window. The simulations reveal that the best attenuation is achieved by placing the control sources away from the edges of the window. It also shows that the plane of control sources can be placed centrally with respect to the depth of the walls, for practical implementation with minimal performance degradation. The simulated attenuation as a function of frequency and window width, for different angles of noise incidence, can be used to provide an estimate of the number of control sources, based on the desired level of attenuation. This estimate helps to determine the configuration with the minimum number of control sources required for different scenarios, before a more detailed system design is undertaken. [ABSTRACT FROM AUTHOR]

Noise pollution has a significant negative effect on psychological health and quality of life. The building envelop, particularly windows often constitute to the primary path for external noise sources to travel into the buildings. Here we have designed and fabricated transparent piezoelectric film speakers as secondary area sound source for active noise mitigation for window application with ventilation function. The performance properties of the obtained transparent speaker and its effectiveness for active noise mitigation are evaluated through numerical simulations as well as experimental measurements. The produced transparent piezoelectric film speaker exhibited enhanced overall sound pressure level (SPL) and broader frequency response range with a significantly improved SPL at frequencies below 300 Hz. Furthermore, compared to an electromagnetic speaker as a point secondary sound source, using the transparent piezoelectric film speaker as an area source resulted in more uniform noise mitigation with substantially larger averaged SPL reduction. The results presented here show the potentials and advantages of transparent piezoelectric film speakers for active noise mitigation. [ABSTRACT FROM AUTHOR]

The open-fit hearing aids that allow air and sound into the ear canal have become popular in recent years. Unfortunately, they result in the noise leakage problem that bypasses the hearing aids toward the eardrum and will degrade the quality of desired signal. This paper proposes a modified audio-integrated adaptive feedback active noise control (ANC) system for open-fit hearing aids. Traditionally, the ANC system attenuates the total power of the unwanted noise over the entire spectrum. To increase efficiency and save power consumption of hearing aids, we design a customized filter based on the hearing threshold of hearing-impaired patient to generate the anti-noise only in audible frequency range. The performance of the proposed method is verified by both computer simulations and real-time experiments. [ABSTRACT FROM AUTHOR]

The traditional active noise control design aims to attenuate the energy of residual noise, which is indiscriminative in the frequency domain. However, it is necessary to retain residual noise with a specified spectrum to satisfy the requirements of human perception in some applications. In this paper, the evolution of active noise control and sound quality are briefly discussed. This paper emphasizes on the advancement of active noise control method in the past decades in terms of enhancing the sound quality. [ABSTRACT FROM AUTHOR]

The functional link artificial neural network (FLANN) structure using trigonometric function expansion is used successfully in nonlinear active noise control (NANC) system. However, there are still two potential shortcomings to deteriorate its performance. One is that the FLANN filter may perform poorly when the cross-terms exist in NANC system, and the other is that the FLANN filter cannot obtain its optimal solution in some complex nonlinear cases because its nonlinear parts have intrinsic coefficient dependences between each other. To surmount these shortcomings, improved FLANN (IFLANN) filter and simplified IFLANN (SIFLANN) filter are proposed in this paper. To reduce the computational complexity further, the filtered-error least mean square (FELMS) algorithm is considered in the NANC system using these two proposed filters. IFLANN and SIFLANN filters solve these problems by inserting a corrective filter before trigonometric function expansion to offer suitable cross-term delay samples and counterbalance the nonlinear coefficients calculation. Moreover, detailed computational complexity analysis and extensive simulations with different reference signal and acoustic path are provided to demonstrate the effectiveness of the proposed IFLANN and SIFLANN filters. Compared to FLANN filter and its other improved versions, the proposed IFLANN and SIFLANN filters have better performance on computational burdens and noise attenuation. [ABSTRACT FROM AUTHOR]

Online feedback path modeling and neutralization (FBPMN) is vital in active noise control (ANC) systems to ensure stability and elevate performance in non-stationary environments. In this paper, we propose a modified variable step size (VSS) method for online FBPMN in single-channel ANC systems which incorporates three adaptive filters; a noise control filter, a FBPMN filter, and a linear predictor for disturbance removal. In the proposed method, distinct VSS LMS algorithms are used for FBPMN filter and disturbance removal filter to achieve exceptionally fast convergence and accurate modeling of the feedback path transfer function. Simulation results show that the proposed method yields a significantly more robust ANC system by attaining a higher gain margin at a much faster rate in comparison with the existing methods. [ABSTRACT FROM AUTHOR]

A Hybrid Active Noise Control (HANC) system is used to attenuate disturbances in a scenario where a portion of noise is captured by reference sensors. In such scenarios, the secondary path continuously changes due to interference by various electrical equipment used in the Active Noise Control (ANC) system. A practical ANC system should be robust to secondary path effects. In existing literature, the secondary path used in a HANC system is estimated offline. In a real time environment, the secondary path is time varying in nature. Hence, Online Secondary Path modeling (OSPM) is a desirable addition to the design of ANC systems because it significantly improves adaptive filter convergence along with better noise reduction performance. In this paper, we propose modified HANC systems with OSPM as continuous modeling of the noise removes the secondary path effects and the HANC system can be used for real time implementation. To achieve this, we extend the OSPM technique from the Eriksson’s method to the conventional HANC system, Sun’s cascading adaptive filters algorithm and Akhtar’s HANC system. Computer simulations prove that the proposed HANC systems with OSPM improves error modeling accuracy and faster convergence against existing HANC systems where the secondary path is modeled offline. The modified HANC framework is also robust to sudden changes in the behaviour of electrical equipment while ANC operation along with providing improved noise cancelling performance. [ABSTRACT FROM AUTHOR]

Since the functional link artificial neural network (FLANN) filter using trigonometric expansions do not exploit cross-terms (products of input samples and /or past output samples with different time shifts), its performance for nonlinear active noise control (ANC) can be considerably degraded, especially in strong nonlinearity environment. In order to overcome this drawback, a novel bilinear FLANN (BFLANN) filter for the nonlinear ANC is proposed in this paper. In addition, a sufficient condition that guarantees the stability of the BFLANN filter is also presented. Simulation results demonstrate that the proposed BFLANN filter based nonlinear ANC can achieve better performance than the FLANN and generalized FLANN (GFLANN) filters based nonlinear ANC in the presence of strong nonlinearity. [ABSTRACT FROM AUTHOR]

This work examines the performance of both offline and online secondary path modeling algorithms that are used in narrowband active noise control (NANC) systems. Theoretical analysis reveals that disturbances that are sensed by error sensors reduce the convergence rate and accuracy of adaptive system identification. In a parallel-structure narrowband active noise control system, a filterbank is applied to partition the full-band excitation and error signals to utilize an independent and lower-order secondary-path modeling filter for every channel. This method increases convergence speed and modeling accuracy. The results of an analysis and improved performance are confirmed by simulations in which measured transfer functions are used. [ABSTRACT FROM AUTHOR]

Active Noise Control (ANC) methods have been successfully applied to the cancellation of stationary noise. Classical ANC systems use adaptive filtering techniques to produce a waveform that is opposite, or counter-phase, to the signal noise we would like to cancel. However, when the noise is of short duration, adaptive filtering cannot be used since convergence is not achieved. In this paper, a novel active control technique for non-stationary noise is presented. The method uses wave field synthesis (WFS) for the construction of the canceling waveform. The system is tailored for an outdoor environment. The noise acoustic field is acquired by microphones and processed by a WFS engine to pilot a linear array of secondary sources. Experimental results, obtained from both simulations and true tests, demonstrate that the proposed method is able to diminish the overall noise perceived in the area covered by the system. [ABSTRACT FROM AUTHOR]

This paper presents an attempt to reduce the computational complexity, while achieving acceptable level of noise reduction in a multi-channel active noise control (MCANC) system for mitigating noise passing through open windows. The reference signals are sensed at the back of the secondary loudspeakers. The existing approach to reduce the computational complexity has already used only one reference signal in each feedforward channel. As the number of error microphones is also important to ensure global noise reduction of the MCANC system for open windows, the main idea of this paper is to preprocess the error signals so that the number of inputs to the controller is further reduced. When the preprocessing is a simple summation, it is called the mixed-error approach. The number of inputs related to the error signals is eventually reduced to 1 after the mixed-error approach is applied. Simulation results demonstrate that the optimum control filters derived under general conditions can lead to similar global noise reduction to those derived based on the mixed-error approach. Experimental results confirm that in a 4-channel MCANC system applied to a 0.2 m by 0.2 m open window, the performance of global noise reduction is not compromised by the mixed-error approach. [ABSTRACT FROM AUTHOR]

Countering mutual coupling in the inherent structures and the non-availability of proper reference or error signals for the operation of adaptive filters has been a challenge in the design of a Hybrid active noise control (HANC) system. Existing HANC systems have not simultaneously addressed these two issues. In this paper, we propose an improved HANC system which generates most appropriate signals for operating the adaptive filters along with decoupling the inherent feedforward and feedback ANC systems in the HANC system. Here, we use an extra adaptive filter which post-processes the error signal to obtain true signals for operating the feedforward control filter which improves the convergence speed and the overall noise reduction. A Joint-Optimized Normalized Least Mean Squares algorithm is employed for generating the true signal by optimizing the system misalignment, which further improves the convergence of the adaptive filter in the feedforward part. The adaptive filter in the feedback structure also gets appropriate signals by internally generating a reference signal which is independent of the feedforward structure. A complete mathematical analysis of the proposed algorithm is done. Simulation results validate the advantages of the proposed system over its counterparts at the cost of increased computational complexity. [ABSTRACT FROM AUTHOR]

• A new diffusion filtered-x least mean squares algorithm for multitask problems. • Variable spatial regularization for diffusion strength control. • Performance analysis for user parameter selection. Distributed multi-channel active noise control (ANC) systems attract a lot of attention due to the reduced computational complexity than centralized control methods and improved stability than decentralized control methods. However, the combination of controllers within a neighborhood in a diffusion manner introduces an estimation bias and may degrade the control accuracy. This is because the secondary sources and error microphones of an ANC system are usually physically placed at different locations and the optimal solution to each controller is different. In this paper, a new diffusion filtered-x least mean squares algorithm (Diff-FxLMS) has been developed that balances combination strength and estimation bias via a variable spatial regularization. The mean squares error criterion subject to a bias constraint is used such that the spatial regularization parameter could be adapted according to the penalized Lagrangian. A detailed performance analysis is carried out, based on which user parameters can be selected automatically. Performance of the proposed variable spatial regularized Diff-FxLMS (VSR-Diff-FxLMS) algorithm and theoretical analysis is verified by simulations. [ABSTRACT FROM AUTHOR]

• A selective active noise control method is proposed to reduce varying noise. • Differential evolutionary algorithm is used to efficiently get parameters of controller. • An online modelling method for primary path in headphones is proposed. • Frequency response matching is introduced into the selection mechanism. • Simulations and experiments verify the performance of proposed selection mechanism. Most active noise control (ANC) headphones operate with a fixed-filter method. When the directions or spectral characteristics of the primary noise fluctuate significantly, the fixed filter exhibits an unsatisfactory noise reduction performance. To address this problem, this study proposes a selective fixed-filter ANC algorithm based on frequency response matching (FRM-SFANC), which chooses a pre-training filter to attenuate variable primary noise. An online modelling approach is adopted to achieve the FRM mechanism. Compared to the conventional fixed-filter method, FRM-SFANC provides superior and robust noise reduction performance. [ABSTRACT FROM AUTHOR]

• A novel generalized hyperbolic secant function with l p -norm algorithm is proposed for nonlinear ANC system. • An improved FsGHSFP (IFsGHSFP) algorithm is developed to address the problem of tuning the parameter. • A convex combination algorithm of IFsGHSFP is suggested to strike a balance between convergence and misalignment. In nonlinear active noise control (ANC) system where the primary noise obeys non-Gaussian distribution, the traditional filter-s least mean square (FsLMS) algorithm is hardly satisfactory. In order to surmount this deficiency, a novel generalized hyperbolic secant function with l p norm (FsGHSFP) algorithm is proposed for nonlinear ANC system, which designs a robust optimization criterion utilizing the generalized hyperbolic secant distribution function. The FsGHSFP algorithm has robust noise attenuation capability for non-Gaussian noise, but suffers from the problem of tuning the parameter. To address this problem, an improved FsGHSFP (IFsGHSFP) algorithm is developed by taking advantage of the fact that continuous mixed norm does not need to adjust norm parameter. Moreover, in order to strike a balance between convergence and misalignment, thereby further enhancing the robustness of the ANC system, a convex combination algorithm of IFsGHSFP is suggested. The robustness mechanism of the proposed algorithms is analyzed, as well as stability conditions and computational complexity. It is verified by simulations that the proposed algorithms accelerate the convergence speed and improve the noise attenuation performance. In addition, the experimental results further validate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

• We investigate a practical active road noise control strategy that can improve the noise attenuation performance according to the selected control position. • The proposed control approach is realized by employing the weighting factor in the error signals to concentrate the control effort for selected seat positions in the vehicle cabin according to the passenger boarding scenario. • The experimental results show that the noise attenuation performance at selected seat positions can be improved by applying and adjusting a weighting factor. This study presents the practical implementation and validation of an automotive active road noise control (ARNC) system that can concentrate control efforts on a selected position by employing a weighting factor in error microphone signals. The current ARNC system is designed to uniformly attenuate road noise across the entire seating position in the vehicle cabin, which results in the abandonment of the ability to maximize noise suppression performance in a single seat. It can be expected that the noise suppression performance of the selected position can be further improved by applying a weighting factor to the error signal to concentrate the control effort. However, practical demonstration of the implementation and evaluation of this approach in modern ARNC systems is scarce. To validate this approach, we investigated the influence of weighting factors in the error signals on the noise suppression performance. A practical active control system was implemented in a large luxury sedan, and the noise attenuation performance according to the weighting factor was evaluated based on real driving experiments. The experimental results show that relatively high weighting factors at the selected location can improve the noise attenuation performance. Moreover, it was found that a small weighting factor of 0.01 is suitable to prevent the acoustic amplification of uncontrolled error microphones, as opposed to the extreme condition where the weighting factor is 0. [ABSTRACT FROM AUTHOR]

• Application of Active noise control in a pump system with variable point of operations for the very first time. • Key technology for smart-grid controlled pump system in order to avoid undesirable pressure pulsation related issues like vibration and noise. Smart-grid control aims to use current power converter technology of pump drives for grid stabilization. Hereby, fluctuations of the power grid frequency are transmitted to the pump drive resulting in pump speed changes. Along with the inherent impeller design these pump speed changes are resulting in pressure pulsations which propagate as hydro acoustic pressure waves throughout the pump system causing noise and vibration issues in the piping system. Therefor, in order to realize smart-grid control, a solution must be found to attenuate or counteract these hydro acoustic pressure waves. In an earlier work [1] , an active noise control (ANC) system to reduce pressure pulsations at a pump's blade passing frequency (BPF) was published with the focus on constant points of operation. However, utilizing smart-grid control will results in high gradients of the pump speed and constantly changing points of operation are to be expected. This paper aims to attack those kinds of operating conditions. Within this paper, moving frequencies of interest at different pump speed gradient with and without active attenuation are analyzed and extracted from time series data by means of Vold-Kalman order tracking filter. In relation to possible fluctuations in the power grids frequency, the active attenuation performance of the ANC system is evaluated. [ABSTRACT FROM AUTHOR]

• A selective perceptual equalization FxLMS (SPE-FxLMS) algorithm is derived. • Residual sounds of the SPE-FxLMS algorithm create a sense of auditory familiarity. • The SPE-FxLMS algorithm is thoroughly examined for a collection of noise types. • The effectiveness of the SPE-FxLMS algorithm is validated in a substation. • Correlations between subjective scores and self-supervised model outputs are found. An active noise control (ANC) system usually contains a control filter to generate an anti-noise sound that destructively interferes with the primary noise. The filtered reference least mean squares (FxLMS) algorithm is the seminal adaptive ANC algorithm that updates the control filter coefficients iteratively. However, the FxLMS algorithm is primarily designed to minimize the power of the residual sound, without consideration to the auditory sensation. Thus, the residual sound can be perceived to be different from the primary noise of a broad frequency band. When an ANC system running the FxLMS algorithm was piloted in a substation's control room, workers expressed discomfort with the residual sound, even though the noise level was reduced. It was mainly because the workers were annoyed by the residual sound which they identified as an anomaly operating state. In order to resolve this problem, this paper proposes a selective perceptual equalization FxLMS (SPE-FxLMS) algorithm to retain the operating state in the residual sound. The simulation, experiment and subjective test results validate the effectiveness of the SPE-FxLMS algorithm in reducing the noise level and shaping the residual sound to create a sense of auditory familiarity for the workers. [ABSTRACT FROM AUTHOR]

Passengers sitting in the back seats of cars while talking on their phones can easily have the privacy of their speech invaded by the driver. One way of protecting speech privacy is to utilize masking sounds, which may also lower speech intelligibility- masking sound may be so loud that it annoys both drivers and speakers. Here, we evaluate the feasibility of utilizing active noise control (ANC), which aims to reduce the level of speech targeted toward the driver, thus lowering the needed level of masking sounds while still protecting speech privacy. Evaluation of speech intelligibility has been completed both objectively and subjectively using Speech Intelligibility Index (SII) and Speech Reception Threshold (SRT), respectively. SII value calculation has shown that ANC is not effective at lowering the level of masking sounds and speech intelligibility. On the other hand, SRT measurement has shown that ANC, which reduces the speech level to around 10 dB below 1000 Hz, is able to lower the level of masking sounds by about 5 dB. [ABSTRACT FROM AUTHOR]

Prior research shows that introducing a reflecting surface near an active control system can improve its noise reduction performance; however the mechanism of the performance improvement is not completely clear. This paper investigates the effects of a reflecting surface on multichannel active sound radiation control systems with a primary monopole source located on the surface. By using a genetic searching algorithm, the locations of secondary sources were optimized to maximize the noise reduction and the frequency range that can be beneficial from the reflecting surface is discussed. It is found that the performance improvement by introducing a reflecting surface is due to the increased sound pressure generated by the secondary sources at the primary source location. The beneficial frequency range extends with the number of the channels of the control system and has an upper limit frequency determined by the distance between the secondary sources and the primary source. Experiments are conducted to validate the results. [ABSTRACT FROM AUTHOR]

Nonlinear active noise control (ANC) algorithms are used to control nonlinear noise processes. In this paper, a generalized filter bank based nonlinear ANC algorithm is proposed for active headrest application. The algorithm is used to control the noise at both ears by using two moving error microphones which are mounted on the head. Mounting of microphones can be made using a wearing item such as a hat or band. Due to this, these microphones move along with the head. The adaptive ANC algorithm is shown to be very effective for head-movement. Real-time implementation of nonlinear ANC algorithm is made using a dSpace 1104 system for both ears. The robust performance of adaptive nonlinear ANC algorithm is shown for controlling nonlinear noise process at both ears even during head movement using a pair of moving error microphones without re-estimating the secondary paths for the new position. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to propose a frequency-domain active noise control algorithm for acoustic noise reduction in magnetic resonance imaging and experimentally verify its feasibility. The sound pressure level of noise approaches up to 130 dB in 3 T magnetic resonance imaging. Even it’s expected to increase for higher-resolution images in the future magnetic resonance. For this noise, some active methods have been researched, but the reduction performance is not enough to satisfy the safety standard. The noise in 3 T magnetic resonance imaging is measured and analyzed in the time-frequency domain. It has fundamental frequency with its higher harmonics, and the Fourier coefficients of all peaks are slowly varying over time. The variation is small enough, so it can be assumed that the noise is periodic in short time. Based on this assumption, the control signal is determined as the sum of sinusoidal signals designed by using the Fourier coefficients calculated from a fundamental period of noise, then it is applied to the next period. To do this in real-time process, domain transform algorithm, which is time to frequency based on discrete Fourier series, is developed with the same level of computational complexity compared to the conventional active noise control algorithm. Experimental results show approximately 35-dB overall reduction in the frequency range of interest (80–1600 Hz). [ABSTRACT FROM AUTHOR]

Nonlinear active noise control (ANC) systems, which employ a nonlinear filter as the adaptive controller is not robust when the primary noise to be mitigated has a non-Gaussian distribution. The algorithm which updates the weights of the controller may even diverge for some higher magnitude primary noise signals. With an objective to improve the robustness of nonlinear ANC systems, a correntropy based nonlinear ANC system is developed in this paper. The proposed ANC scheme uses an information theoretic learning approach and has been shown to provide robust noise mitigation even for non-Gaussian primary noise signals. [ABSTRACT FROM AUTHOR]

Planar virtual sound barriers with secondary sources over the entire opening have been demonstrated an effective way to achieve global control of sound transmission through the opening, but loudspeakers in the middle of the opening affect ventilation, lighting and normal access through it. To avoid the problem, this technical note proposes to implement secondary sources at the edge of a cavity opening and investigates the active sound reduction performance of the system numerically and experimentally. Unlike secondary sources over the entire opening which can achieve sound reduction at any frequency as long as there are sufficient of them, there exists an upper bound of effective frequency for global control when secondary sources are at the edge of the opening; however, local control is always achievable. Preliminary experiments were conducted on an open wooden box and a semi-closed meeting room to support the conclusions. [ABSTRACT FROM AUTHOR]