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

Zijie Shen, Lin Tang and Li Yang

Mathematical Problems in Engineering, 2021, vol. 2021, 1-11

Abstract:

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 L 0 norm constraint SSS-NSAF (S L 0 -SSS-NSAF), sigmoid step-size scaler improved proportionate NSAF (S-SSS-IPNSAF), and sigmoid L 0 norm constraint step-size scaler improved proportionate NSAF (S L 0 -SSS-IPNSAF), is derived by inserting the logarithm cost function into the sigmoid function structure as well as the L 0 norm of the weight coefficient vector to act as a new cost function. Since the use of the fix step size in the proposed S L 0 -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 S L 0 -SSS-IPNSAF (CS L 0 -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.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:9924179

DOI: 10.1155/2021/9924179

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