Minor component analysis with implementation to blind 2-channel equalization

Author

Luo, Jie ; Ling, Xieting

Author_Institution

Fudan Univ., Shanghai, China

Volume

4

fYear

1997

fDate

9-12 Jun 1997

Firstpage

2235

Abstract

A null space method is proposed for blind identification of non-minimum phase linear time-variant channels using minor component analysis. The algorithm is proved to be globally convergent in discrete domain. The fast convergence speed makes this algorithm very useful for tracing a time-variant channel in mobile communication. Some simulations are given to show its tracking ability, and a very efficient method for equalizing the blind channel is also proposed

Keywords

convergence of numerical methods; eigenvalues and eigenfunctions; equalisers; identification; mobile communication; neural nets; statistical analysis; time-varying channels; blind channel; blind equalization; blind identification; discrete domain; eigenvalues; globally convergence; minor component analysis; mobile communication; neural network; nonminimum phase channels; null space learning; time-variant channel; Blind equalizers; Communication channels; Computer simulation; Convergence; Eigenvalues and eigenfunctions; Mobile communication; Neural networks; Null space; Signal processing; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks,1997., International Conference on

Conference_Location

Houston, TX

Print_ISBN

0-7803-4122-8

Type

conf

DOI

10.1109/ICNN.1997.614375

Filename

614375