Details

Autor(en) / Beteiligte

• Habibi, Zahra
• Zayyani, Hadi
• Abadi, Mohammad Shams Esfand

Titel

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

Ist Teil von

• Journal of systems engineering and electronics, 2021-04, Vol.32 (2), p.487-497

Ort / Verlag

Research Institute for Information and Communications Technologies,Academic Center for Education,Culture and Research,Tehran 1599616313,Iran%Department of Electrical and Computer Engineering,Qom University of Technology,Qom 371951519,Iran%Faculty of Electrical Engineering,Shahid Rajaee Teacher Training University,Tehran 1678815811,Iran

Erscheinungsjahr

2021

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• 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.