A Recursive Blind Adaptive Identification Algorithm and Its Almost Sure Convergence

Author

Radenkovic, Miloje S. ; Bose, Tamal

Author_Institution

Colorado Univ., Denver

Volume

54

Issue

6

fYear

2007

fDate

6/1/2007 12:00:00 AM

Firstpage

1380

Lastpage

1388

Abstract

This paper presents a novel blind adaptive identification algorithm based on least-squares type arguments. Parameter estimates are recursively updated with each output measurement, without resorting to any matrix inversion operation. It is proved that the parameter estimates converge almost surely (a.s.) toward a scalar multiple of the true parameters. Possible application of this algorithm to the channel equalization problem is discussed.

Keywords

adaptive equalisers; blind equalisers; channel estimation; least squares approximations; recursive estimation; blind adaptive identification; channel equalization; convergence; least-squares type arguments; parameter estimates; recursive algorithm; scalar multiple; Adaptive equalizers; Antenna measurements; Blind equalizers; Convergence; Eigenvalues and eigenfunctions; Higher order statistics; Parameter estimation; Receiving antennas; Recursive estimation; Signal processing; Almost sure eigenvalue; blind adaptive identification; blind equalization; recursive parameter estimation;

fLanguage

English

Journal_Title

Circuits and Systems I: Regular Papers, IEEE Transactions on

Publisher

ieee

ISSN

1549-8328

Type

jour

DOI

10.1109/TCSI.2007.895522

Filename

4232597