Title
Variable Explicit Regularization in Affine Projection Algorithm: Robustness Issues and Optimal Choice
Abstract
A variable regularized affine projection algorithm (VR-APA) is introduced, without requiring the classical step size. Its use is supported from different points of view. First, it has the property of being Hinfin optimal and it satisfies certain error energy bounds. Second, the time-varying regularization parameter is obtained by maximizing the speed of convergence of the algorithm. Although we first derive the VR-APA for a linear time invariant (LTI) system, we show that the same expression holds if we consider a time-varying system following a first-order Markov model. We also find expressions for the power of the steady-state error vector for the VR-APA and the standard APA with no regularization parameter. Particularly, we obtain quite different results with and without using the independence assumption between the a priori error vector and the measurement noise vector. Simulation results are presented to test the performance of the proposed algorithm and to compare it with other schemes under different situations. An important conclusion is that the former independence assumption can lead to very inaccurate steady-state results, especially when high values of the projection order are used
Year
DOI
Venue
2007
10.1109/TSP.2007.893197
IEEE Transactions on Signal Processing
Keywords
Field
DocType
error vector,measurement noise vector,optimal choice,variable explicit regularization,steady-state error vector,proposed algorithm,former independence assumption,inaccurate steady-state result,different point,different situation,certain error energy bound,affine projection algorithm,different result,robustness issues,adaptive filter,vectors,satisfiability,markov model,linear time invariant,convergence,adaptive filtering,first order,steady state,markov processes,adaptive filters,noise measurement,robustness,linear time invariant system,regularization,steady state analysis,testing
Affine transformation,LTI system theory,Mathematical optimization,Markov process,Noise measurement,Markov model,Control theory,Robustness (computer science),Regularization (mathematics),Rate of convergence,Mathematics
Journal
Volume
Issue
ISSN
55
5
1053-587X
Citations 
PageRank 
References 
40
3.03
15
Authors
4
Name
Order
Citations
PageRank
H. Rey127418.90
L.R. Vega21086.02
S. Tressens326918.38
Jacob Benesty41941146.01