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Fast generalized affine projection algorithm
Author(s) -
Sankaran Sundar G.,
Louis Beex A. A.
Publication year - 2000
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/1099-1115(200009)14:6<623::aid-acs607>3.0.co;2-0
Subject(s) - convergence (economics) , algorithm , affine transformation , projection (relational algebra) , flexibility (engineering) , computer science , mathematics , mathematical optimization , statistics , pure mathematics , economics , economic growth
The affine projection algorithm (APA), and the entire class of algorithms equivalent to APA, attempts to accelerate the convergence of the normalized least‐mean‐squares (NLMS) algorithm by adapting weights based on past input vectors in addition to the usual NLMS adaptation based on the current input vector. Before deriving a fast version of it, we review our generalized APA algorithm called NLMS with orthogonal correction factors (NLMS‐OCF). NLMS‐OCF provides complete flexibility in choosing the past input vectors. This flexibility provides improved convergence over the APA and its equivalents. A fast version of NLMS‐OCF is then derived which uses a lattice‐based forward–backward predictor. The significant convergence properties of NLMS‐OCF are summarized. Simulation results that compare NLMS‐OCF and APA are presented. Copyright © 2000 John Wiley & Sons, Ltd.