Augmented Set-membership Affine Projection Algorithm and Its Performance Analysis

TL;DR

This paper introduces ASM-APA, a low-complexity, improved version of AAPA for colored signals, with stability analysis and superior performance demonstrated through simulations.

Contribution

The paper proposes ASM-APA, combining set-membership filtering with affine projection, reducing complexity and enhancing performance over existing AAPA methods.

Findings

ASM-APA has lower computational complexity than AAPA.

ASM-APA demonstrates improved performance in simulations.

Stability conditions for ASM-APA are derived.

Abstract

The augmented affine projection algorithm (AAPA) has considerably excellent performance for highly colored input signals. However, the direct matrix inversion operation leads to a high computational complexity, especially with high projection order. Inspired by the excellent characteristics of set-membership filtering (SMF), this paper proposes the augmented set-membership affine projection algorithm (ASM-APA), which not only has low computational complexity but also offers improved performance compared with AAPA. Then, the computational complexity and stability of ASM-APA are analyzed, and the condition for maintaining the stability of the algorithm is provided. Finally, in the computer simulation phase, the results of the simulation experiments demonstrated that ASM-APA has superior performance compared to AAPA.