A Unified Analysis Approach for LMS-based Variable Step-Size Algorithms
Data Structures and Algorithms
2017-03-22 v1
Abstract
The least-mean-squares (LMS) algorithm is the most popular algorithm in adaptive filtering. Several variable step-size strategies have been suggested to improve the performance of the LMS algorithm. These strategies enhance the performance of the algorithm but a major drawback is the complexity in the theoretical analysis of the resultant algorithms. Researchers use several assumptions to find closed-form analytical solutions. This work presents a unified approach for the analysis of variable step-size LMS algorithms. The approach is then applied to several variable step-size strategies and theoretical and simulation results are compared.
Cite
@article{arxiv.1501.02487,
title = {A Unified Analysis Approach for LMS-based Variable Step-Size Algorithms},
author = {Muhammad Omer Bin Saeed},
journal= {arXiv preprint arXiv:1501.02487},
year = {2017}
}
Comments
5 pages, 1 figure, 5 tables