NDLI: A block LMS-type algorithm with a function controlled variable step-size for sparse system identification

Content Provider	IEEE Xplore Digital Library
Author	Turan, C. Salman, M.S. Eleyan, A.
Copyright Year	2015
Description	Author affiliation: Electr. & Electron. Eng. Dept., Mevlana (Rumi) Univ., Konya, Turkey (Turan, C.; Salman, M.S.; Eleyan, A.)
Abstract	Block least-mean-square algorithm has a very fast processing time compared to the conventional LMS algorithm. This is due to the updating mechanism of the filter coefficients. Filter coefficients are updated for each sample input for the LMS algorithm. This process is faster with BLMS algorithm as the filter coefficients are updated for blocks of the input sequence instead. The BLMS algorithm can also be improved in the same manner as LMS by using different approaches such as variable step-size and/or sparsity. This paper proposes a new BLMS-type algorithm with a function controlled variable step-size LMS for sparse system identification. The performance of the proposed algorithm is compared to that of the BLMS algorithm in terms of convergence rate and mean-square-deviation. The effects of the filter length, sparsity degree and signal-to-noise ratio (SNR) on MSD were also investigated. Simulations prove that the proposed algorithm always outperforms the BLMS algorithm.
Starting Page	1
Ending Page	4
File Size	295042
Page Count	4
File Format	PDF
ISBN	9789531842099
DOI	10.1109/ELMAR.2015.7334481
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-28
Publisher Place	Croatia
Access Restriction	Subscribed
Rights Holder	Croatian Society Electronics in Marine - ELMAR
Subject Keyword	Algorithm design and analysis Mean-Square-Deviation Adaptive systems Least squares approximations FC-VSSLMS Algorithm System Identification Signal processing algorithms Approximation algorithms Acoustics Block LMS Algorithm Signal to noise ratio
Content Type	Text
Resource Type	Article

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