DCD-Based Recursive Adaptive Algorithms Robust Against Impulsive Noise

Yu, Yi; Lu, Lu; Zheng, Zongsheng; Wang, Wenyuan; Zakharov, Yuriy; Lamare, Rodrigo C. de

doi:10.1109/tcsii.2019.2936407

Cited by 31 publications

(15 citation statements)

References 24 publications

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“…To generate û(n), the proposed algorithm demands 2L-point FFT, its inverse FFT, and 2L complex multiplications for (3), which leads to 8 log 2 (2L)+8 multiplications and 8 log 2 (2L) additions in total. In addition, QN multiplications and (Q − 1)N additions are required for ũi (n), and Q multiplications and (Q − 1) additions are required for ẽi,D (k).…”

Section: Tablementioning

confidence: 99%

Delayless Block Individual-Weighting-Factors Sign Subband Adaptive Filters With an Improved Band-Dependent Variable Step-Size

et al. 2020

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Delayless individual-weighting-factors sign subband adaptive filter (IWF-SSAF) algorithms with a band-dependent variable step-size (BDVSS) were recently introduced to achieve a robust convergence performance against the impulsive interference and to avoid an undesirable signal path delay in subband systems. In this paper, we develop a block implementation of the delayless IWF-SSAF algorithm designed for an active impulsive noise control (AINC) system. With the block-processing approach, the proposed delayless block IWF-SSAF algorithm can be implemented more efficiently than the original delayless algorithm regardless of number of subbands, which is verified through the computational analysis. Furthermore, an improved BDVSS version (I-BDVSS) is also proposed by using the multiple auxiliary past gradients, which are given for each band by the block-processing. Finally, the simulation results illustrate that the proposed delayless block IWF-SSAF algorithm with the I-BDVSS, even requiring less computational burden, can achieve a better convergence performance than the original delayless algorithm with the BDVSS under severe impulsive noise control environment.INDEX TERMS Delayless structure, individual-weighting-factors sign subband adaptive filter, block implementation, active impulsive noise control, band-dependent variable step-size.

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Section: Tablementioning

confidence: 99%

Delayless Block Individual-Weighting-Factors Sign Subband Adaptive Filters With an Improved Band-Dependent Variable Step-Size

et al. 2020

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“…In the second example, the uniform noise and impulsive noise are used as the noise signal, and in the third example, the exponential and impulsive noises are employed as the noise signal. The impulsive noise is generated by Bernoulli-Gaussian (BG) distribution, which contains a Bernoulli process and Gaussian process [11], [62] ζ (k) = B e (k)G a (k) (38) where B e denotes a Bernoulli process with the probability P r , which can be defined by P(B e ) = 1 − P r with B e = 0, and P(B e ) = P r with B e = 1, and G a (k) stands for a white Gaussian process with zero mean and variance σ 2 ζ . To qualify the identification performance of the algorithm, both excess MSE (EMSE) and normalized MSD (NMSD) are adopted in the simulations, which can be respectively defined as EMSE, db = 10log 10 e 2 a (k)…”

Section: Simulationsmentioning

confidence: 99%

Affine Projection Algorithm by Employing Maximum Correntropy Criterion for System Identification of Mixed Noise

Wang

Han

2019

IEEE Access

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The adaptive algorithms have been widely studied in Gaussian environment. However, the impulsive noise and other non-Gaussian noise may largely deteriorate the performance of algorithm in practical applications. To address this problem, in this paper, we propose two novel adaptive algorithms for system identification problem with mixed noise scenarios. Both proposed algorithms are based on the framework of the affine projection (AP) algorithm. The first proposed algorithm, termed as VS-APMCCA, combines variable step-size (VS) strategy and maximum correntropy criterion (MCC) to obtain improved performance. For further performance improvement, the VC-VS-APMCCA is developed, which is based on the variable center (VC) scheme of MCC. The convergence analysis of the VC-VS-APMCCA is conduced. Finally, simulation results demonstrate the superior performance of the VS-APMCCA and VC-VS-APMCCA. INDEX TERMS Affine projection algorithm, variable step-size, maximum correntropy criterion (MCC), variable center (VC), mixed noise.

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“…Adaptive filtering is famous for its numerous practical applications, such as system identification, acoustic echo cancellation, channel equalization, and signal denoising [1][2][3][4][5]. Due to easy complementation and low computational complexity, the least mean square (LMS) algorithm and the normalized least mean square (NLMS) algorithm become distinguished.…”

Section: Introductionmentioning

confidence: 99%

Robust Normalized Subband Adaptive Filter Algorithm with a Sigmoid-Function-Based Step-Size Scaler and Its Convex Combination Version

Shen

Tang

Yang

2021

Mathematical Problems in Engineering

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In this paper, by inserting the logarithm cost function of the normalized subband adaptive filter algorithm with the step-size scaler (SSS-NSAF) into the sigmoid function structure, the proposed sigmoid-function-based SSS-NSAF algorithm yields improved robustness against impulsive interferences and lower steady-state error. In order to identify sparse impulse response further, a series of sparsity-aware algorithms, including the sigmoid L0 norm constraint SSS-NSAF (SL0-SSS-NSAF), sigmoid step-size scaler improved proportionate NSAF (S-SSS-IPNSAF), and sigmoid L0 norm constraint step-size scaler improved proportionate NSAF (SL0-SSS-IPNSAF), is derived by inserting the logarithm cost function into the sigmoid function structure as well as the L0 norm of the weight coefficient vector to act as a new cost function. Since the use of the fix step size in the proposed SL0-SSS-IPNSAF algorithm, it needs to make a trade-off between fast convergence rate and low steady-state error. Thus, the convex combination version of the SL0-SSS-IPNSAF (CSL0-SSS-IPNSAF) algorithm is proposed. Simulations in acoustic echo cancellation (AEC) scenario have justified the improved performance of these proposed algorithms in impulsive interference environments and even in the impulsive interference-free condition.

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DCD-Based Recursive Adaptive Algorithms Robust Against Impulsive Noise

Cited by 31 publications

References 24 publications

Delayless Block Individual-Weighting-Factors Sign Subband Adaptive Filters With an Improved Band-Dependent Variable Step-Size

Delayless Block Individual-Weighting-Factors Sign Subband Adaptive Filters With an Improved Band-Dependent Variable Step-Size

Affine Projection Algorithm by Employing Maximum Correntropy Criterion for System Identification of Mixed Noise

Robust Normalized Subband Adaptive Filter Algorithm with a Sigmoid-Function-Based Step-Size Scaler and Its Convex Combination Version

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