Variable Step-Size NLMS and Affine Projection Algorithms

Shin, Hyun-Chool; Sayed, Ali H.; Song, Woo‐Jin

doi:10.1109/lsp.2003.821722

Cited by 475 publications

(304 citation statements)

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“…To improve noise immunity under Gaussian noise, the squared autocorrelation of errors at adjacent time was used in [14], and in [15], the fourth-order cumulant of instantaneous error was adopted. Important examples of two new variable step-size (VSS) versions of the NLMS and the APA algorithm (APA) can be found in [16]. In [16], the norm of the projected weighted error vector is used as a criterion to determine how close the adaptive filter is to optimum performance.…”

Section: Introductionmentioning

confidence: 99%

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A Family of Variable Step-Size Affine Projection Adaptive Filtering Algorithms

Abadi¹,

Mehrdad²,

Gholipour³

et al. 2010

IJCEE

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Abstract-This paper presents a family variable step-size (VSS) affine projection (AP) adaptive filtering algorithms with good convergence speed and low steady state mean square error features. In the following, the family of VSS selective partial updates (SPU) affine projection algorithms are established which reduce the computational complexity. The stability bounds of the family of APA and SPU-APA algorithms are analyzed based on the energy conservation arguments. This analysis does not need to assume a Gaussian or white distribution for the regressors. We demonstrate the good performance of the proposed algorithms through simulations in system identification and acoustic echo cancellation scenarios.Index Terms-Adaptive filter, affine projection, selective partial update, variable step-size, stability analysis.

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Section: Introductionmentioning

confidence: 99%

“…Important examples of two new variable step-size (VSS) versions of the NLMS and the APA algorithm (APA) can be found in [16]. In [16], the norm of the projected weighted error vector is used as a criterion to determine how close the adaptive filter is to optimum performance.…”

Section: Introductionmentioning

confidence: 99%

A Family of Variable Step-Size Affine Projection Adaptive Filtering Algorithms

Abadi¹,

Mehrdad²,

Gholipour³

et al. 2010

IJCEE

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“…By optimally selecting the step-size during the adaptation, we can obtain both fast convergence rates and low steadystate MSE. In [9], a new variable step-size NLMS (VSS-NLMS) algorithm was proposed. In this algorithm, the step-size changes to obtain the largest decrease in MSD during the iterations [9].…”

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confidence: 99%

“…In [9], a new variable step-size NLMS (VSS-NLMS) algorithm was proposed. In this algorithm, the step-size changes to obtain the largest decrease in MSD during the iterations [9]. In this paper, we extend the approach in [9] to NSAF, and SPU-NSAF algorithms and VSS version of these algorithms are proposed.…”

mentioning

confidence: 99%

“…In this algorithm, the step-size changes to obtain the largest decrease in MSD during the iterations [9]. In this paper, we extend the approach in [9] to NSAF, and SPU-NSAF algorithms and VSS version of these algorithms are proposed. We demonstrate the good performance of the presented algorithms through several simulation results in a system identification scenario.…”

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The New Normalized Subband Adaptive Filter Algorithms with Variable Step-Size

Abadi

Shafiee

2014

Automatika

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Original scientific paperThis paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. In the proposed VSS-NSAF, the step-size changes in order to have largest decrease in the mean square deviation (MSD) for sequential iterations. To reduce the computational complexity of VSS-NSAF, the variable step-size selective partial update normalized subband adaptive filter (VSS-SPU-NSAF) is proposed. In this algorithm the filter coefficients are partially updated in each subband at every iteration. Simulation results show the good performance of the proposed algorithms in convergence speed and steady-state MSD.

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