Search

This work proposes an algorithm for feedback ANC that does not require a prior secondary path model and usually remains stable after fast secondary path changes, as other algorithms proposed for feedforward ANC. This is achieved using a recursive least squares algorithm to model the secondary path and the primary noise with an autoregressive moving average model. The resulting model allows for predicting future values of the primary noise. Finally, the primary noise values predicted are filtered by a non-causal inverse of the secondary path model to generate the anti-noise signal. Simulation results attest to the validity of the algorithm in reducing narrowband noise. [ABSTRACT FROM AUTHOR]

Summary: In feedforward active noise and vibration control (ANVC) or active noise control (ANC), with online secondary path modeling, fast converging overall modeling algorithms may give high modeling errors. These errors are due to the highly correlated inputs, namely the reference and antinoise signals. These high modeling errors can result in poor performance if ignored. However, it is possible to consider these modeling errors in the control filter design, resulting in a careful controller and good performance, as proposed in this work. Careful control is a dual controller feature, which is the solution to the optimal control problem, but this has not been proposed before in the context of ANC. The modeling error covariance matrix (Sigma(n)) is available in the Kalman filter. However, this requires the knowledge of the time‐varying measurement noise power q(n) and state noise. Instead, this work uses a different approach in which the corresponding linear system is solved in a non‐recursive manner. The resulting maximum error is used for a worst‐case estimate of q(n), and, as it turns out, this can be used to get a worst‐case estimate of Sigma(n). A lower control filter update frequency and other optimizations keep computational complexity similar to other approaches. The resulting algorithm has very few easily selected parameters, good performance, does not require any prior secondary path estimate, and adapts to slow and sudden changes in the physical paths without loss of performance or noise overshoots. However, performance can be impaired by large background noise levels. [ABSTRACT FROM AUTHOR]

Most digital active noise controllers have an intrinsic delay due to reconstruction and anti-aliasing filters. These delays may make them less attractive when compared with analog implementations. This delay is critical for broadband active noise control performance, even though the same is not valid in the narrowband case. The delay can be reduced by using custom design filters for the application with large transition bands but cannot be made close to zero. Also, the sampling rate can be increased, but this causes a significant increase in the computational cost since the number of control filter output calculations per second increases and the size of the control filter increases. This work proposes a way to reduce these delays almost to zero without a substantial increase in the computational cost by using the quantization and noise shaping techniques used in sigma-delta analog-to-digital (AD) and digital-to-analog (DA) converters. Sigma-delta AD and DA converters are used but without the typical filter. The controller filter impulse response is also oversampled, and the resulting filter is implemented at a high frequency but using just a few bits, resulting in low computational complexity. The AD downsampling filter and the DA reconstruction are not needed because noise shaping moves the quantization error to high frequencies that are not audible and that are filtered naturally by the acoustic transducers. However, standard adaptive filtering algorithms working at a low sampling frequency are still used to choose the control filter. [ABSTRACT FROM AUTHOR]

Summary: The mirror‐modified filtered‐x least mean squares (MMFxLMS) algorithm is a variation of the FxLMS algorithm with online secondary path modeling that cannot diverge due to secondary path modeling errors. However, problems may occur when the ambient noise is not limited due to insufficient modeling power. This work shows that under a frequency domain analysis without ambient noise, the MMFxLMS algorithm is always stable, and expressions for the maximum residual noise level at any given time are obtained. It is also shown that, under the same context, convergence to the minimum residual noise is guaranteed. Still, convergence can be much slower for high secondary path modeling errors than that of the LMS or MFxLMS algorithms. Simulations confirm these results. [ABSTRACT FROM AUTHOR]

This work describes the log-MAP (BCJR) algorithm implementation of a close to capacity dirty paper coding CODEC. The CODEC consists of eight deep pipeline processors. It decodes blocks of 975 bits in 26.9 ms using less than 9.7% of low-cost FPGA (and no DSP blocks). Two pipelines, for alpha and beta, calculate the values of gamma (of the BCJR) to reduce the storage requirements. The final log-likelihood ratio (LLR) is calculated together with alpha, reusing intermediate results. The number of bits used by the different signals of the processor is easily configurable. It was set to six bits to the channel measure signals and eight bits to log of probability signals like alpha, beta, and others. The CODEC clock was 100 MHz. The achieved bit rate is 36.2 Kbps per CODEC, but multiple CODECs can be fit into a single chip. The CODEC is 3.49 dB from the channel capacity. [ABSTRACT FROM AUTHOR]

Summary: Most active noise control (ANC) algorithms require a model of the secondary path (SP). If there are large changes in the SP, online SP modeling algorithms may not be able to follow the changes quickly enough to prevent divergence. In this work, the mirror‐MFxLMS (MMFxLMS) is adapted to narrowband ANC, and the resulting algorithm is analyzed. The MMFxLMS is an algorithm similar to the MFxLMS and FxLMS but has online SP modeling; it is stable for any SP estimate and does not require auxiliary noise. In addition, a technique to alternate between MFxLMS and MMFxLMS is proposed, resulting in the M3FxLMS algorithm, which does not sacrifice performance and assures stability. However, the M3FxLMS requires a reference signal that is not available in feedback ANC. Feedback ANC is important in many practical cases, for instance, in ANC headphones. To solve this problem, a technique is proposed to synthesize a reference formed by a sum of sinusoids using measurements from the error sensor signal. This technique uses the fast Fourier transform to obtain estimates of the harmonic frequencies of the periodic noise components, and then refines and tracks these using a phase‐locked loop (PLL). The resulting algorithm enables a stable ANC system, even under large and sudden changes in the SP. The proposed PLL is also new and has a lock‐in range equal to the full band of the system. [ABSTRACT FROM AUTHOR]

Power-line communication (PLC) allows establishing digital communications without adding any new wires. It will turn one's house or neighborhood grid into a smart grid. PLC has some issues, namely, high noise at low frequencies and varying characteristic impedance. This paper addresses these issues to improve the signal-to-noise ratio by increasing the signal or reducing the noise. PLC MODEMs are subject to legislations that limit the signals in the line. The radiated signal is proportional to the current, but not to the input current, since the current forms a standing wave along the line. However, better performance can be achieved if the input current is measured. The receiver circuit of the transmitting MODEM can be used to estimate the input impedance. This paper presents a technique to use this new information to achieve better performance and to follow legislation changes in the band above 30 MHz. A study of the viability of using impulsive noise reduction techniques to further increase performance is also presented. The short noise pulses result in high correlation between the noises in different carriers. Impulse position detection should result in an increase in capacity. [ABSTRACT FROM AUTHOR]

This paper proposes techniques for the extraction of biological information in a recently developed handheld biochip-based microsystem. The microsystem is based on a mag- netoresistive array biochip composed of a number of sensing sites with magnetic tunneling junctions (MTJ) and diodes. Different techniques are addressed to drive the MTJs with different types of signals. Different filtering strategies that allow the recovery of biological signals from the noise without overly increasing either the time required for accessing the sensors or the power consumption of the board are proposed. Finally, new techniques and algorithms are proposed to deal with the variability of the fabrication parameters of the MTJ and the diodes. Experiments with the system in a setup to detect actual biological signals are presented with encouraging results. [ABSTRACT FROM AUTHOR]

A fully integrated biochip based on a 16 × 16 scalable matrix structure of aluminum oxide magnetic tunnel junctions (MTJs) and thin-film diodes (TFDs of hydrogenated amorphous silicon) was fabricated and included as the biosensor of a portable handheld microsystem developed for biomolecular recognition detection using magnetic labels [deoxyribonucleic acid (DNA) hybridization, antibody antigen interaction, etc.]. The system uses magnetic field arraying of magnetically, tagged biomolecules and can potentially be used to detect single or few biomolecules. Each biosensor matrix node is the series between a TFD (p-i-n or Schottky-barrier type) and an MTJ. In this paper, this matrix basic cell biosensor element is completely characterized and modeled. Experimental measured data are provided and compared with the proposed theoretical models results. It is shown that the diode may be used both as the matrix switching device and as an in-site temperature sensor and that the MTJ may act as the magnetoresistive sensor for detecting the fringe field of immobilized magnetic markers. Therefore, the fabricated fully integrated biochip included in the developed handheld microsystem may be used for biomolecular recognition. [ABSTRACT FROM AUTHOR]