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An optimized ZA-LMS algorithm for time varying sparse system

Authors
  • Radhika, S.1
  • Arumugam, Chandrasekar2
  • 1 Sathyabama University, School of Electrical and Electronics, Chennai, India , Chennai (India)
  • 2 St. Joseph’s College of Engineering, Department of Computer Science, Chennai, India , Chennai (India)
Type
Published Article
Journal
International Journal of Speech Technology
Publisher
Springer US
Publication Date
May 03, 2019
Volume
22
Issue
2
Pages
441–447
Identifiers
DOI: 10.1007/s10772-019-09616-7
Source
Springer Nature
Keywords
License
Yellow

Abstract

The zero attracting least mean square algorithm has improved performance than conventional LMS when the system is sparse and its performance decreases when the sparsity level is decreased or when the system is time varying. The proposed algorithm focused on optimization of both step size and zero attractor controller using state variable model to improve the overall performance at all sparsity levels. Simulations in the context of time varying sparse system identification proved that the proposed algorithm provides good performance when compared to the conventional ones.

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