L2-Stability Analysis of The Set-Membership Affine Projection Algorithm
Rajab Shabaani
TL;DR
This paper proves that the set-membership affine projection algorithm is inherently stable in the l2 sense, ensuring it never diverges regardless of parameter choices, with simulations supporting the analysis.
Contribution
The paper provides the first stability analysis of the SM-AP algorithm, demonstrating its guaranteed l2-stability under all parameter settings.
Findings
SM-AP algorithm is l2-stable
Algorithm never diverges regardless of parameters
Simulation results confirm theoretical analysis
Abstract
In this letter, we study the local and the global robustness of the set-membership affine projection (SM-AP) algorithm. We demonstrate that the SM-AP algorithm has l2-stability. In fact, the SM-AP algorithm never diverges; no matter how the parameters of the SM-AP algorithm has been adopted. Finally, the simulation results substantiate the validity of the proposed analysis.
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Taxonomy
TopicsAdvanced Adaptive Filtering Techniques · Blind Source Separation Techniques · Image and Signal Denoising Methods