Robust normalized subband adaptive filter algorithm against impulsive noises and noisy inputs

DOI10.1016/J.JFRANKLIN.2020.02.032zbMath1451.93399OpenAlexW3007303082MaRDI QIDQ1989319

Zongsheng Zheng, Xiaobing Lu, Zhigang Liu

Publication date: 21 April 2020

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2020.02.032

zbMATH Keywords

system identificationsubband adaptive filterimpulsive noise environments

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Sensitivity (robustness) (93B35) System identification (93B30)

Related Items (4)

Mixture quantized error entropy for recursive least squares adaptive filtering ⋮ Sparsity-aware normalized subband adaptive filters with jointly optimized parameters ⋮ A new mathematical model for reconstruction ECG signal based on non-polynomial cubic spline ⋮ A family of variable step-size sparsity-aware SSAF algorithms with individual-weighting-factors under model-driven method

Cites Work

• Low-complexity non-uniform penalized affine projection algorithm for sparse system identification
• Collaborative adaptive Volterra filters for nonlinear system identification in \(\alpha\)-stable noise environments
• Sparse normalized subband adaptive filter algorithm with \(l_0\)-norm constraint
• A family of proportionate normalized subband adaptive filter algorithms
• Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments
• Kernel recursive generalized mixed norm algorithm
• Augmented complex-valued normalized subband adaptive filter: algorithm derivation and analysis
• Sparse adaptive channel estimation based on mixed controlled \(l_2\) and \(l_p\)-norm error criterion
• Mean-Square Deviation Analysis of Multiband-Structured Subband Adaptive Filter Algorithm
• Stabilization of a Bias-Compensated Normalized Least-Mean-Square Algorithm for Noisy Inputs
• Robust Statistics

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