Variable step-size normalized LMS algorithm by approximating correlation matrix of estimation error
SCIE
SCOPUS
- Title
- Variable step-size normalized LMS algorithm by approximating correlation matrix of estimation error
- Authors
- Cho, H; Kim, SW
- Date Issued
- 2010-09
- Publisher
- ELSEVIER SCIENCE BV
- Abstract
- In this letter, we propose a variable step-size normalized least mean square (NLMS) algorithm. We study the relationship among the NLMS, recursive least square and Kalman filter algorithms. Based on the relationship, we derive an equation to determine the step-size of NLMS algorithm at each time instant. In steady state, the convergence of the proposed algorithm is verified by using the equation, which describes the relationship among the mean-square error, excess mean-square error, and measurement noise variance. Through computer simulation results, we verify the performance of the proposed algorithm and the change in the variable step-size over iterations. (C) 2010 Elsevier B.V. All rights reserved.
- Keywords
- Variable step-size; Normalized least mean square algorithm; Kalman filter; Recursive least square; State-space equation; AFFINE PROJECTION ALGORITHMS; MEAN-SQUARE
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/25620
- DOI
- 10.1016/J.SIGPRO.2010.03.027
- ISSN
- 0165-1684
- Article Type
- Article
- Citation
- SIGNAL PROCESSING, vol. 90, no. 9, page. 2792 - 2799, 2010-09
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