Bradley Department of Electrical & Computer EngineeringVirginia Tech
Title Relative convergence of the cascade RLS with subsection adaptation algorithm
Author(s) G. Zakaria and A. A. (Louis) Beex
Document Type Conference Proceeding
Conference Thirty-Third Asilomar Conference on Signals, Systems, and Computers
Publication Information Volume 1, Pages 810 - 814
Conference Date 24 - 27 October 1999
Document Download Available
Abstract

We analyze the convergence behavior of the CRLS-SA algorithm for inverse filtering. The CRLS-SA is a cascade adaptive filter based on the RLS algorithm, with each section adapted independently based on global minimization. The subsection adaptation results in reduced computational complexity. The rate of convergence is evaluated based on the convergence time constant defined as the ratio of condition number and sensitivity. The smaller the convergence time constant, the faster the structure converges. Analysis and simulation explain and show that CRLS-SA exhibits faster convergence than the direct form RLS adaptive filter for speech type signals.

Keywords
  • Adaptive Filters
  • Relative Convergence
  • Cascade RLS
  • Subsection Adaptation Algorithm
  • Convergence Behavior
  • CRLS-SA Algorithm
  • Inverse Filtering
  • Cascade Adaptive Filter
  • RLS Algorithm
  • Reduced Computational Complexity
  • Direct Form RLS Adaptive Filter
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