A robust subband adaptive filter algorithm for sparse and block-sparse systems identification

• 来源期刊: 系统工程与电子技术（英文版）
• 年，卷（期）: 2021,（2）
• 所属期刊栏目: CONTROL THEORY AND APPLICATION
• 页码范围: 487-497
• 页数: 11页
• 语种: 英文
• DOI: 10.23919/JSEE.2021.000041

摘要

This paper presents a new subband adaptive filter (SAF) algorithm for system identification scenario under impuls-ive interference, named generalized continuous mixed p-norm SAF (GCMPN-SAF) algorithm. The proposed algorithm uses a GCMPN cost function to combat the impul- sive interference. To further accelerate the convergence rate in the sparse and the block-sparse system identification processes, the proportionate versions of the proposed algorithm, the L0-norm GCMPN-SAF (L0-GCMPN-SAF) and the block-sparse GCMPN-SAF (BS-GCMPN-SAF) algorithms are also developed. Moreover, the convergence analysis of the proposed algorithm is provided. Simulation results show that the proposed algorithms have a better performance than some other state-of-the-art algorithms in the literature with respect to the convergence rate and the tracking capability.