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

Abstract

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.

Normalized frequency‐domain block sign algorithm using ℓ1$\ell _{1}$‐norm minimization

“…Figure 3 shows the comparison of the proposed VSS‐NFBSA with other algorithms in the same experimental environment as in Figure 2. The comparison adaptive filters were combinations of the widely used adaptive filters and VSS algorithms to be robust against impulsive noise: the combined step‐size NSA (CSS‐NSA) [18] robust VSS decorrelation NLMS (RVSS‐DNLMS) [31], robust VSS APSA (RVSS‐APSA) [32], improved band‐dependent VSS delayless individual‐weighting‐factors SSAF (IBDVSS‐IWF‐SSAF) [4]. Furthermore, we used the step‐size control (SSC) method [33], which operates in the frequency domain, with the NFBSA to demonstrate the superiority of the proposed VSS algorithm.…”

“…Introduction: Real-world adaptive filtering applications suffer severe impairments from background and impulsive noises, causing filter coefficient instability or divergence [1][2][3][4][5]. To mitigate impulsive interference, the sign algorithms (SA) and normalized SA (NSA) are used, which can be implemented as additional sign operations to the least-mean-square (LMS) and normalized LMS (NLMS) algorithms, respectively.…”

Stochastic Behaviour Analysis of Adaptive Averaging Step-size Sign Normalised Hammerstein Spline Adaptive Filtering

“…In order to reduce the computational requirements of NLMS, the simplifications of NLMS approach in the form of a sign algorithm has been presented in several applications [11]- [16]. To further diminish and protect the impulse noise, the sign normalised SAF [11], [12] and sign subband adaptive filterings with variable step-size parameter [13]- [15] have been designed. In [16], the robust shrinkage normalised version of sign algorithm has been implemented.…”