A Complete Transient Analysis for the Incremental LMS Algorithm
Muhammad Omer Bin Saeed
TL;DR
This paper provides a comprehensive transient analysis of the incremental LMS algorithm, including its learning behavior, and verifies the theoretical results with experimental data.
Contribution
It offers the first complete transient analysis of the ILMS algorithm, filling a gap left in prior research.
Findings
Transient behavior characterized and analyzed
Theoretical results validated by experiments
Enhanced understanding of ILMS learning dynamics
Abstract
The incremental least mean square (ILMS) algorithm was presented in \cite{Lopes2007}. The article included theoretical analysis of the algorithm along with simulation results under different scenarios. However, the transient analysis was left incomplete. This work presents the complete transient analysis, including the learning behavior. The analysis results are verified through several experimental results.
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Taxonomy
TopicsAdvanced Adaptive Filtering Techniques · Blind Source Separation Techniques · Speech and Audio Processing