A fast convergence normalized least‐mean‐square type algorithm for adaptive filtering
Authors:
- 31 July 2013
- journal article
- research article
- Published by Wiley in International Journal of Adaptive Control and Signal Processing
- Vol. 28 (10) , 1073-1080
Abstract
SUMMARY: A new adaptive algorithm with fast convergence and low complexity is presented. By using the calculation structure of the dual Kalman variables of the fast transversal filter algorithm and a simple decorrelating technique for the input signal, we obtain an algorithm that exhibits faster convergence speed and enhanced tracking ability compared with the normalized least‐mean‐square algorithm with similar computational complexity. Copyright © 2013 John Wiley & Sons, Ltd.Keywords
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