Blind source recovery for non-minimum phase surroundings

Author

Waheed, Khurram ; Salem, Fathi M.

Author_Institution

San Diego State Univ., CA, USA

Volume

5

fYear

2004

fDate

23-26 May 2004

Abstract

This paper revisits the issue of blind source recovery (BSR) of non-minimum phase linear MIMO systems and provides a new rigorous derivation of the proposed state space algorithms by K. Waheed and F.M. Salem (2002), K. Waheed F.M. Salem (2003) and L.Q. Zhang et al. (1999). Using state space representation for both the mixing and convolving (or reverberative) surrounding environment and recovery (or demixing and deconvolving) networks, we systematically derive update laws based on the minimization of Kullback-Liebler divergence using the theory of optimization and the calculus of variations along the Riemannian contra-variant (or the natural) gradient. A simulation example for recovery of signals from a challenging non-minimum environment is also included in this paper.

Keywords

FIR filters; MIMO systems; blind source separation; gradient methods; optimisation; state-space methods; transfer functions; Kullback-Liebler divergence; MIMO systems; Riemannian contravariant gradient; blind source recovery; convolving surrounding environment; mixing surrounding environment; nonminimum phase linear systems; nonminimum phase surroundings; optimization theory; recovery networks; signal recovery; state space algorithms; state space representation; Calculus; Computer networks; Filtering theory; Finite impulse response filter; IIR filters; MIMO; Poles and zeros; State-space methods; Transfer functions; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2004. ISCAS '04. Proceedings of the 2004 International Symposium on

Print_ISBN

0-7803-8251-X

Type

conf

DOI

10.1109/ISCAS.2004.1329451

Filename

1329451