Analysis of Variable Step-size Order Statistic LMS-based Algorithms with a Data-reuse Factor

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Published: Jun 28, 2013
Keywords:
Adaptive filters variable step-size algorithm order statistic mechanism least mean square (LMS) algorithm data-reuse factor

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Suchada Sitjongsataporn
Centre of Electronic Systems Design and Signal Processing (CESdSP), Department of Electronic Engineering, Mahanakorn University of Technology
Kodchakorn Na Nakornphanom
School of Science and Technology, Sukhothai Thammathirat Open University

Abstract

In this paper, we present variable step-size algorithms based on an order statistic normalized averaged least mean square (OS-NALMS) with a data-reuse factor. An optimal step-size parameter is investigated by means of mean square deviation criterion, we then modify in the recursion form. Two of new variable step-size approaches are introduced with regard to the optimal step-size algorithm. In order to reduce the complexity, a variable data-reuse factor approach is applied to the number of reused gradient based estimate sequences for averaged least mean square algorithm. Simulation results demonstrate that the performance of proposed variable step-size OS-NALMS algorithms can obtain in terms of fast convergence and robustness.

Article Details

Issue
Vol. 16 No. 1 (2013): January - June 2013
Section
Research Articles

Copyright @2021 Engineering Transactions 

Faculty of Engineering and Technology

Mahanakorn University of Technology

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