期刊论文详细信息
Journal of Global Research in Computer Sciences | |
A PERFORMANCE ANALYSIS OF LMS, RLS AND LATTICE BASEDALGORITHMS AS APPLIED TO THE AREA OF LINEAR PREDICTION | |
article | |
Nasrin Akhter1  Lilatul Ferdouse1  Fariha Tasmin Jaigirdar1  Tamanna Haque Nipa1  | |
[1] Department OF Computer Science, Stamford University Bangladesh | |
关键词: Adaptive filtering; Linear Prediction; LMS; RLS; Lattice based algorithms; SNR.; | |
来源: Research & Reviews | |
【 摘 要 】
This paper presents a performance analysis of three categories of adaptive filtering algorithms in the application of linear prediction. The classes of algorithms considered are Least-Mean-Square (LMS) based, Recursive Least-Squares (RLS) based and Lattice based adaptive filtering algorithms. The performances of the algorithms in each class are compared in terms of convergence behavior, execution time and filter length. The analysis determines the best converging algorithm from each class. Finally the best performing algorithm for adaptive linear prediction is selected.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO202307140002367ZK.pdf | 128KB | download |