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In neuroscience, time-frequency analysis is widely used to investigate brain rhythms in brain recordings. In event-related protocols, it is applied to quantify how the brain responds to a stimulation repeated over many trials. We here focus on two common measures: the power of the transform for each single trial averaged across trials, avgPOW; and the power of the transform of the average evoked potential, POWavg. We investigate the influence of additive noise on these two measures. We quantify the expected effect using theoretical calculations, simulated data and experimental brain recordings. We also consider the case of color noise. We extract the main factors influencing the effect of noise on POWavg and avgPOW, such as the noise variance, the number of trials, the sampling rate, the type of noise, the type of time-frequency transform and the frequency of interest. When dealing with time-frequency analysis, the impact of noise on the neuroscientist's work can drastically vary depending on these factors. The present results should help researchers improve their understanding and interpretation of time-frequency diagrams, as well as optimize their experimental designs and analyses based on their neuroscientific question.

Three-dimensional printers are increasingly used in design work when designers want to quickly and inexpensively verify their solutions. However, based on the sounds made by the printer during its operation, it is possible to determine the shape of the printed object with quite high accuracy. The above fact should be taken into account if information about this object needs to be protected. The article presents a way to protect a 3D (Three-Dimensional) printer against acoustic infiltration. The research study was carried out using the Zortrax M200 Plus printer for LPD (Layer Plastic Deposition) technology, which is an equivalent of the popular FDM/FFT (Fused Deposition Modeling/Fused Filament Fabrication) 3D printing technology using thermoplastic. The frequencies of acoustic signals related to the operation of stepper motors and the printing platform were identified. These signals enable the reconstruction of the shape of printed objects. It was examined whether the appropriate type and required level of masking noise can be selected for a given type of printer in order to protect it against acoustic infiltration. The masking properties of selected color noises were compared with those of white noise and the optimal intensity levels were determined at which the acoustic safety of the tested printer can be ensured. It was underlined that the research results refer only to the tested printer and should not be generalized to other types of 3D printers. [ABSTRACT FROM AUTHOR]

Subject and Purpose. Designers of the research radars intended for detecting manifestations of biological activity of living organisms may be interested in the noise characteristics shown by their oscillators at offsets about 10–2 Hz or even 10–3Hz from the carrier frequency. Unfortunately, the producing companies do not practice regular information on noise performance of their products at frequencies below 1 Hz. The present authors have set the goal of deriving an analytical expression for the spectral density of flicker noise which should allow radar engineers estimating the probable noise performance of low-noise oscillators over any frequency range. Methods and Methodology. A great number of writers considering spectral properties of flicker noise tend to support the assertion that its spectral density increases continuously with a decrease in frequency, following the power law 1/f. Meanwhile, the present authors assume availability of a certain frequencyfmbelow which the spectral density should most likely remain unchanged, even to as low as zero frequency. Also, there is a range of frequencies above which the spectral density of flicker noise remains constant and the total spectral density is determined solely by thermal noise. Results.The spectral density of noise follows the power law 1/f throughout the range fromfm and up to the point where thermal noise starts to overbalance the flicker noise. The authors have proposed an approximating function to describe the behavior of the averaged spectral density of noise from the oscillator within the entire frequency range. Conclusions. The results obtained shall allow radio system designers to make estimates of the probable noise performance of low-noise oscillators in any frequency range, using only known reference data provided by the manufacturer.

We explore numerically the complex dynamics of multilayer networks (consisting of three and one hundred layers) of cubic maps in the presence of noise-modulated interlayer coupling (multiplexing noise). The coupling strength is defined by independent discrete-time sources of color Gaussian noise. Uncoupled layers can demonstrate different complex structures, such as double-well chimeras, coherent and spatially incoherent regimes. Regions of partial synchronization of these structures are identified in the presence of multiplexing noise. We elucidate how synchronization of a three-layer network depends on the initially observed structures in the layers and construct synchronization regions in the plane of multiplexing noise parameters "noise spectrum width – noise intensity". It is shown that in a hundred-layer network, clusters of synchronized layers can be formed at certain optimal values of multiplexing noise parameters. The performed numerical studies confidently indicate that the spatial dynamics of multilayer networks can be controlled by varying multiplexing noise parameters. • Partial synchronization in multilayer networks depends on initial spatial structures. • Clusters of synchronized layers can be formed at optimal values of multiplexing noise. • Spatial dynamics of multilayer networks can be controlled by multiplexing noise. [ABSTRACT FROM AUTHOR]

As the demand for low-power electronics and IoT devices grows, ambient energy harvesting appears to be a promising alternative for powering such systems in the long run. However, optimizing power and efficiency concurrently in such systems is challenging, involving balancing a number of variables. This paper investigates the optimization of power and efficiency in ambient energy harvesting systems focusing on nonlinear oscillator electromechanical harvesters subjected to multiplicative time-correlated ambient noise. Through extensive numerical simulations, we reveal distinct relationships between power and efficiency, influenced by various parameters. We observe autonomous stochastic resonance phenomena, elucidating a linear power-efficiency trend for small noise correlation time under fixed noise variance but limiting simultaneous power and efficiency optimization beyond a threshold. Under fixed noise strength, there is a trade-off between power and efficiency. Additionally, damping strength, piezoelectric parameters, and capacitor charging time impact power and efficiency linearly. These insights enhance understanding of power efficiency dynamics in ambient energy harvesting, thereby offering practical recommendations for parameter selection to maximize both power output and efficiency in the next generation of electronics. • The power-efficiency dynamics of the ambient energy harvester is investigated. • Autonomous stochastic resonance phenomenon is studied in nonlinear energy harvester. • Power and efficiency follow linear as well as trade-off relationships. • Practical recommendations for optimizing both power and efficiency is offered. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the response of asymmetric potential monostable energy harvesters (MEHs) excited by color noise and band-limited noise. The motivation for this study is that environmental vibrations always have the characteristic of randomness, and it is difficult to modulate a perfectly symmetric MEH. For the excitation of exponentially correlated color noise, the moment differential equation was applied to evaluate the output performance of the asymmetric potential MEHs. Numerical and theoretical analyses were carried out to investigate the influence of noise intensity and internal system parameters on the output power of the system. Our results demonstrate that the output performance of the asymmetric MEH decreases with the increase in the correlation time, which determines the character of the color noise. On the contrary, the increase in the asymmetric degree enhances the output power of the asymmetric MEH subjected to color noise. For the band-limited noise excitation, numerical simulation is undertaken to consider the response of the asymmetric MEHs, and outcomes indicate that the frequency bandwidth and center frequency have a significant influence on the output performance. Regarding the asymmetric potential, its appearance leads the MEHs to generate higher output power at lower frequencies and this phenomenon is more obvious with the increase in the degree of asymmetry. Finally, we observed that the characteristics of the response bandwidth of asymmetric MEHs subjected to band-limited noise excitation are similar to the response under harmonic excitation. [ABSTRACT FROM AUTHOR]

Can the Dual-Sequence-Frequency-Hopping (DSFH) as a military emergency communication mode work under strong color noise? And is there any detection improvement of the DSFH signal via stochastic resonance (SR) processing under color noise? To deal with this problem, we analyze the physical feature of the DSFH signal. Firstly, the signal models of transmission, reception and the intermediate frequency (IF) are constructed. And the scale transaction is used to adjust the IF signal to fit the SR. Secondly, the non-markovian Langevin Equation (LE) is transformed into a markovian one by expand the 1-D LE to~a 2-D one. Thirdly, the non-autonomous Fokker-Plank Equation (FPE) is transformed into an autonomous one by assuming that the SR transition of magnetic particles is instantaneous and introducing the decision time. Therefore, the analytical periodic steady solution of the probability density function (PDF) with the parameter of the correlation time of the color noise is obtained. Finally, the detection probability, false alarm probability and Receiver Operating Characteristics (ROC) curve are obtained, under the criterion of the maximum~a posterior probability (MAP). Theoretical and simulation results show as below: 1) whether the DSFH can work under strong color noise is decided by the correlation time of the color noise; 2) when the power intensity of the color noise is constant, the smaller the correlation time with the bigger local SNR, the greater PDF difference of the SR output under two hypothesis, leading to better detection performance.

Radio signals in wireless communication apart from information exchange are used for various other real-time applications like localization, tracking, security etc, so their accurate reconstruction is required. Traditional modeling of wireless signals considers only white noise components along with channel fading & propagation channel effects while in practice, there also exist some colored noise component due to environmental disturbances & internal electronic system, which leads to erroneous measurement/reconstruction. In this paper, we analyze statistical properties of such colored noise components and show that the colored noise components are also present in received radio signal along with white noise. These colored noise components are time-dependent and should necessarily be considered in case of the fixed position of transmitter and receiver, as in this case, the time-varying component is the colored noise component, being distance fixed. We further analyzed the contribution of each component in degrading the BER performance of the system. Our results confirm the significant degradation of BER performance of the communication system in presence of colored noise components and so they should be considered while processing received radio signals.

The traffic congestion and accidents can be relieved by deploying the software defined internet of vehicles (SDN-IoV). However, the traffic of pedestrians and vehicles is particularly heavy near commercial streets and campuses. In particular scenarios, the SDN-IoV may not ensure the quality of service (QoS) for pedestrians and vehicles. In this paper, we construct a novel system architecture consisting of multiple non-cooperative unmanned aerial vehicles (UAVs) and a SDN-IoV. The non-cooperative UAV is equipped with an antenna array to receive the signals from the vehicles and pedestrians of SDN-IoV. In order to locate the positions of vehicles and pedestrians, two source enumeration methods are proposed in a complex SDN-IoV environment with color noise. The projection matrix of the low dimensional signal subspace is constructed by the proposed criterion based on signal subspace projection (SSP). The sequence of the projected difference values of the local covariance matrix is applied to estimate the number of vehicles and pedestrians. The eigenvalues can be grouped to construct different subspaces by the proposed eigen-subspace projection (ESP). By projecting a new covariance matrix into the eigen-subspaces, the variance of values represents the projection difference can be exploited to estimate the number of vehicles and pedestrians. Simulation results and real system test verify the validity of the two proposed methods by comparing them with the state-of-the-art methods. Both of the methods have excellent estimation performance especially in color noise. [ABSTRACT FROM AUTHOR]

In this work, we present a method to explore the landscape of a smooth potential in the search of global minimizers, combining a double-descent technique and a basin-escaping technique based on intermittent colored diffusion. Numerical results illustrate the performance of the method. [ABSTRACT FROM AUTHOR]

This article proposes a square-root (SR) extended instrumental variable (EIV) projection approximation subspace tracking (PAST) algorithm with variable forgetting factor (VFF) and variable regularization (VR). A new local polynomial modeling (LPM) based VFF is proposed by minimizing the mean squares deviation of the EIV linear model and the IV-PAST algorithm. A new variable $\ell 2$ regularization term is also derived to reduce the variance of the estimator resulting from possibly ill conditioned covariance matrix at low input signal level. An SR version of the algorithm is developed to improve the numerical stability of the algorithm and avoid the problem of loss of positive definiteness of the inverse covariance matrix. The proposed LOFF-VR-SREIV-PAST algorithm can be implemented by both the conventional EIV-PAST algorithm and numerically more stable hyperbolic rotations. Furthermore, the convergence of the proposed VFF-EIV-PAST algorithm using the ordinary differential equation method is analyzed. Its application to the estimation and tracking of direction of arrival under spatial color sensor noise in both stationary and nonstationary scenarios are presented. Simulations demonstrate that the proposed algorithm yields improved performance over the conventional PAST and EIV-PAST algorithms, especially at medium to low signal-to-noise ratio, which is more frequently encountered in practical situations. [ABSTRACT FROM AUTHOR]

• Use local PSD to weaken the influence of noise spectral lines. • A pre-whitening technology is proposed to deal with colored noise. • TDMD still shows good performance in signals with SNR = −24.9 dB. • Achieve out-of-band and in-band noise cancellation. Difference mode decomposition (DMD) is an ideal decomposition method that can accurately separate the signal into fault components, natural components, and noise. However, DMD is proposed based on the assumption that the amplitude of the noise spectral line is 0, and it cannot analyze the signal with a low signal-to-noise ratio (SNR). To expand the application scenarios of DMD, the two-stage difference mode decomposition method (TDMD) is proposed for diagnosing rolling bearing and gear faults. The sum of the amplitudes of the power spectral density in a certain frequency band is expressed as the spectral line of the local power spectral density (LPSD). Taking advantage of that LPSD can weaken the influence of noise spectral lines covering fault spectral lines, inputting LPSD into the convex optimization function can locate the noise frequency band. Set the spectrum lines in the noise frequency band to zero, and preliminarily eliminate noise interference. Inputting the noise-reduced normalized spectrum to the convex optimization function can accurately extract the fault components. The proposed method can effectively eliminate noise bands and highlight the main different spectral lines between healthy signals and fault signals. Simulation and experimental verification show that this method can effectively analyze signals with a low SNR. TDMD still shows good performance in signals with SNR = −24.9 dB. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the response of asymmetric potential monostable energy harvesters (MEHs) excited by color noise and band-limited noise. The motivation for this study is that environmental vibrations always have the characteristic of randomness, and it is difficult to modulate a perfectly symmetric MEH. For the excitation of exponentially correlated color noise, the moment differential equation was applied to evaluate the output performance of the asymmetric potential MEHs. Numerical and theoretical analyses were carried out to investigate the influence of noise intensity and internal system parameters on the output power of the system. Our results demonstrate that the output performance of the asymmetric MEH decreases with the increase in the correlation time, which determines the character of the color noise. On the contrary, the increase in the asymmetric degree enhances the output power of the asymmetric MEH subjected to color noise. For the band-limited noise excitation, numerical simulation is undertaken to consider the response of the asymmetric MEHs, and outcomes indicate that the frequency bandwidth and center frequency have a significant influence on the output performance. Regarding the asymmetric potential, its appearance leads the MEHs to generate higher output power at lower frequencies and this phenomenon is more obvious with the increase in the degree of asymmetry. Finally, we observed that the characteristics of the response bandwidth of asymmetric MEHs subjected to band-limited noise excitation are similar to the response under harmonic excitation.

Can the Dual-Sequence-Frequency-Hopping (DSFH) as a military emergency communication mode work under strong color noise? And is there any detection improvement of the DSFH signal via stochastic resonance (SR) processing under color noise? To deal with this problem, we analyze the physical feature of the DSFH signal. Firstly, the signal models of transmission, reception and the intermediate frequency (IF) are constructed. And the scale transaction is used to adjust the IF signal to fit the SR. Secondly, the non-markovian Langevin Equation (LE) is transformed into a markovian one by expand the 1-D LE to a 2-D one. Thirdly, the non-autonomous Fokker-Plank Equation (FPE) is transformed into an autonomous one by assuming that the SR transition of magnetic particles is instantaneous and introducing the decision time. Therefore, the analytical periodic steady solution of the probability density function (PDF) with the parameter of the correlation time of the color noise is obtained. Finally, the detection probability, false alarm probability and Receiver Operating Characteristics (ROC) curve are obtained, under the criterion of the maximum a posterior probability (MAP). Theoretical and simulation results show as below: 1) whether the DSFH can work under strong color noise is decided by the correlation time of the color noise; 2) when the power intensity of the color noise is constant, the smaller the correlation time with the bigger local SNR, the greater PDF difference of the SR output under two hypothesis, leading to better detection performance. [ABSTRACT FROM AUTHOR]

This work presents the process of physical crosslinking of hyaluronic acid (HA) in the presence of phospholipids (PL) as applied to the lubrication in articular cartilage system. Three time scales of the process have been studied using Molecular Dynamics simulation: 2 ps, 200 ps and 20 ns. The simulations were carried out for long and short chains of HA in the presence and in the absence of PL. We show that in contrast to the macroscopic thermal (white) noise, the short-time noise on the molecular scale has the properties of color noise with the power spectrum distribution proportional to the inverse of frequency, PSD ∼ 1 ∕ f α . The long-time simulations are characterized by a power spectrum similar to that of white noise. [ABSTRACT FROM AUTHOR]

In response to the challenge of the complex environment such as non-cooperative communication and wide-band electromagnetic spectrum regulation, where existing missing priori information, serious channel distortion and un-even color noise in frequency domain, a novel spectrum sensing algorithm based on multi-scale power spectral density subband gradient(MPSG)was proposed. The proposed algorithm, not relying on any prior information, calculated gra-dients of sections for the power spectrum and detected the narrowband signals by adaptive double threshold, which im-proved the stability of wideband spectrum sensing through multi-scale technique. Theoretically expressions of statistical properties, false alarm probability, detection probability and decision threshold in different channels were deduced. The theoretical analysis and simulation results prove that the novel algorithm overcomes effectively the color noise with low computational complexity and strong real-time in Gaussian noise and fading channel, which can accomplish occupying band range localization of prime users. In addition, the proposed algorithm is robust for noise varia uncertainty, even in the low SNR environment.

We consider the classical deterministic susceptible-infective-susceptible epidemic model, where the infection and recovery rates depend on a background environmental process that is modeled by a continuous time Markov chain. This framework is able to capture several important characteristics that appear in the evolution of real epidemics in large populations, such as seasonality effects and environmental influences. We propose computational approaches for the determination of various distributions that quantify the evolution of the number of infectives in the population. [ABSTRACT FROM AUTHOR]

Control engineers are interested in state estimation problems as one of the most interesting subject. In this way, Kalman filter, H-infinity, and Mixed Kalman/H-infinity filter are the most widely used filters for state estimation of the discrete linear dynamical system corrupted with Gaussian and white noises. These filters will be, however, suboptimal for state estimation when the process noise and/or measurement noise are color noises. In this paper, a multi-objective Pareto optimization(multi-objective genetic algorithm) approach is presented for the design of combined Kalman/H-infinity filters to estimate states corrupted with color noises. In this way, a state augmentation procedure is used to analyze the effect of the colored noises on states estimation of an inverted pendulum. Some Pareto curves are then obtained to compromise between the Kalman and H-infinity filters. It is shown that the use of such approach can evidently improve the effectiveness of the filters when the color noises are significant. Therefore, by using the proposed approach, we can employ the advantages of both Kalman and H-infinity filters simultaneously to minimize both the mean of squared errors and the upper bounds limit of estimation errors. [ABSTRACT FROM AUTHOR]

Abstract: Red-Green-Blue (RGB) photoelasticity has become popular recently owing to its ability for determining the isochromatic fringe orders by processing a single photoelastic color image. This technique employs an a priori calibrated RGB look-up table (LUT) for demodulation of colors in the analyzed image based on an error function. The demodulation is based on the minimization of the error function, which sometimes produce ambiguous fringe orders. Therefore, the initially proposed error function was improved by regularized (or refined) schemes for ambiguity-free isochromatic demodulation. The simplest regularized scheme employs horizontal scanning and left pixel fringe order continuity to remove ambiguity. This particular scheme cannot produce noise-free fringe maps in the presence of color abberations (discontinuities or noise) at the starting pixels of the rows. The available literature mostly deals with the removal of ambiguities produced due to minimization of the error function. This paper highlights the noise produced in the fringe maps due to the presence of color abberations at the starting pixels. To address this issue, an alternative scheme is proposed, wherein a modified regularized algorithm and an improved LUT calibration have been employed in tandem. Moreover, two other schemes, which are meant for ambiguity removal, have been explored for removing the color noise. The present work is observed to produce smooth and accurate fringe maps without any manual intervention to the fringe map. [Copyright &y& Elsevier]

In this paper, we propose a noise reduction algorithm for digital color images using a nonlinear image decomposition approach. Most existing noise reduction methods do not adequately consider spatial correlation of color noise in digital color images. Color noise components in color images captured by digital cameras are observed as irregular grains with various sizes and shapes, which are spatially randomly distributed. We use a modified multiscale bilateral decomposition to effectively separate signal and mixed-type noise components, in which a noisy input image is decomposed into a base layer and several detail layers. A base layer contains strong edges, and most of noise components are contained in detail layers. Noise components in detail layers are reduced by an adaptive thresholding function. We obtain a denoised image by combining a base layer and noise-reduced detail layers. Experimental results show the effectiveness of the proposed algorithm, in terms of both the peak signal-to-noise ratio and visual quality. [ABSTRACT FROM AUTHOR]

The ionization and the dissociation of the diatomic molecular ion H have been investigated within a scheme where a noise field is added to an intense infrared laser field. The results show that both the ionization and the dissociation probabilities are enhanced with the introduction of the additional noise (the Gaussian white noise or the color noise) field. Further, by tuning the noise intensity and the delay time between the laser and the noise, a stochastic resonancelike curve is observed for the ionization or the dissociation dynamics, showing the existence of an optimal noise intensity and delay time for the given laser field. [ABSTRACT FROM AUTHOR]

Abstract: The paper reports a detailed analysis of the chaotic dynamics of a theoretical model of a time delayed semi conductor laser. The periodic, quasi-periodic and chaotic nature is investigated with phase-plots, bifurcation analysis and lyapunov exponents. The effect of the system when induced by colored and bounded sine-Wiener noise has been examined extensively. The nature of the noise-induced propagating waves is investigated with the help of wavelet power spectra. It has been observed that the additive noise can suppress the chaotic dynamics of the system. Also the system is more chaotic in the presence of multiplicative noise. Moreover, the additive and multiplicative noise can modulate the output power upto a certain level, with constant input parameters. [Copyright &y& Elsevier]

In this paper, we investigated the influence of color noise on pattern formation in a predator-prey model. When the model has no noise, it exhibits wave dynamics. A series of numerical simulations showed that break-up of waves will emerge when noise is added. Furthermore, stationary pattern can be induced by noise. The obtained results may point out that noise can have great effect on spatial complexity of ecosystems. [ABSTRACT FROM AUTHOR]

Making use of the theory of maximum likelihood estimation (MLE), a new multipath estimation method based on colored noise Kalman filter to estimate GPS multipath signal is put forward. A linear model of correlation outputs for multipath estimation based on Kalman filtering was built. The state equation and observation equation of Kalman filter were deduced when the observed noise was colored noise, and the generation process of colored noise was explained. The recursive formula of Kalman filter was deduced, which was used to execute iterative filtering of MLE output. Experimental results show that the new design has better performance than MLE, and it can get the precise estimation of multipath signal under 20 dB · Hz of CNR [ABSTRACT FROM AUTHOR]

An approach based on stochastic particle swarm optimization was applied for the mathematical processing of spectral profiles with noise. To test the algorithm’s stability with respect to noise, we used the noises with different values of the Hurst index which characterizes noise component from the point of view of prevalence of low-frequency or high-frequency component in it. The Hurst index varied from 0.1 to 0.9. An influence of color noise with level from 1 to 10% on processing of optical signals by particle swarm optimization algorithm was analyzed. This method is shown to be stable with respect to noise with the level of 10% if it’s the Hurst index does not exceed the value of 0.5.

• Investigated paced walking with visual cues. • Cues were pink or white noise and with a normal or uniform probability distribution. • Gait influenced by both temporal pattern and the probability distribution of visual cues. • The sensorimotor system has an affinity to pink noise and normal distributions. The structure of the stride-to-stride time intervals during paced walking can be altered by the temporal pattern of the pacing cues, however, it is unknown if an altered probability distribution of these cues could also affect stride-to-stride time intervals. We investigated the effect of the temporal pattern and probability distribution of visual pacing cues on the temporal structure of the variability of the stride-to-stride time intervals during walking. Participants completed self-paced walking (SPW) and walking paced by visual cueing that had a temporal pattern of either pink noise presented with a normal distribution (PNND), shuffled pink noise presented with a normal distribution (SPNND), white noise presented with a normal distribution (WNND), and white noise presented with a uniform distribution (WNUD). The temporal structure of the stride-to-stride time intervals was quantified using the scaling exponent calculated from Detrended Fluctuation Analysis. The scaling exponent was higher during the SPW and PNND trials than during the SPNND, WNND and WNUD trials and it was lower during the WNUD trial compared to the SPNND trial. The results revealed that both the temporal pattern and the probability distribution of the visual pacing cues can affect the scaling exponent of the variability of the stride-to-stride time intervals. This information is fundamental in understanding how visual input is involved in the control of gait. [ABSTRACT FROM AUTHOR]

An efficient method for equalization of downlink CDMA channels is presented. By describing the observed signal in terms of a state-space model, the method employs the Kalman filter (KF) to achieve an unbiased signal estimate satisfying the linear minimum mean-squared error (LMMSE) criterion. The state-space model is realized at the symbol and chip levels. With the symbol-level model, the KF is used to estimate the transmitted chips that correspond to each symbol interval; whereas at the chip level, the transmitted chips are estimated individually. The symbol-level KF has a built-in tracking capability that takes advantage of the a priori known scrambling sequence, which renders the transmitted signal nonstationary. The chip-level KF reduces the complexity of the symbol-level KF significantly by ignoring the nonstationarity introduced by scrambling. A simple method for further reducing the KF complexity is also presented. The computational complexity of the proposed technique is analyzed and compared with that of several linear approaches based on finite-impulse response (FIR) filtering. Simulations under realistic channel conditions are carried out which indicate that the KF-based approach is superior to FIR equalizers by - in error-rate performance.

Summary: Achieving security in the Internet of things (IoT) networks by generating symmetric keys from the wireless channel parameters like received signal strength (RSS) is a promising approach. Despite the easy acquisition of the RSS signal, RSS‐based security is less explored for IoT. In this work, we analyze the performance of RSS‐based wireless physical layer key generation with correlated colored noise components and proposed a low complexity filtering approach to improve the performance for the IoT network. We started with providing a survey of various recent researches related to RSS‐based key generation and also discussed correlated colored noise components with a few of the recent works considering them. Further, we analyze various colored noise components in the time domain by the Allan variance and Ljung‐Box test. Furthermore, we develop a key generation model and proposed a moving window averaging‐based filtering followed by Lloyd max quantization to improve the BDR performance, degraded due to the presence of correlated colored noise components. The simulation results show that the proposed preprocessing technique has a considerable improvement in the BDR performance, and the keys generated have sufficient randomness, which is verified by NIST test. [ABSTRACT FROM AUTHOR]