Enhanced line search applied to blind channel identification identifiability conditions

Author

Rajih, Myriam ; Comon, Pierre

Author_Institution

I3S Lab.

fYear

2005

fDate

17-20 July 2005

Firstpage

829

Lastpage

834

Abstract

The ALS algorithm, used to fit the PARAFAC model, sometimes needs a large number of iterations before converging. The slowness in convergence can be due to the large size of the data, or to the presence of degeneracies, etc. Several methods have been proposed to speed up the algorithm, some of which are compression (R. Bro and C.A. Andersson, 1998), and line search (R. Bro, 1998). In M. Rajih and P. Comon (2005) presents a novel method for speeding up the algorithm, enhanced line search (ELS), that shows better results in simulations compared to the existing methods, especially in the case of degeneracy. This paper gives an application of ELS to blindly identify the mixing matrix of an under-determined mixture (UDM): algorithm ALESCAF, and states the identifiability conditions based on ALESCAF

Keywords

channel allocation; matrix algebra; search problems; ALESCAF; PARAFAC model; blind channel identification; enhanced line search; identifiability conditions; under-determined mixture; Argon; Convergence; Laboratories; Least squares methods; Matrix decomposition; Principal component analysis; Psychometric testing; Signal processing algorithms; Singular value decomposition; Tensile stress;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on

Conference_Location

Novosibirsk

Print_ISBN

0-7803-9403-8

Type

conf

DOI

10.1109/SSP.2005.1628708

Filename

1628708