A new unsupervised neural learning rule for orthonormal signal processing

Author

Fiori, Simone ; Campolucci, Paolo ; Uncini, Aurelio ; Piazza, Francesco

Author_Institution

Dipt. di Elettronica e Autom., Ancona Univ., Italy

Volume

4

fYear

1997

fDate

21-24 Apr 1997

Firstpage

3349

Abstract

We derive a new class of neural unsupervised learning rules which arises from the analysis of the dynamics of an abstract mechanical system. The corresponding algorithms can be used to solve several problems in the area of digital signal processing, where orthonormal matrices are involved. We present an application which deals with blind separation of sources, i.e. a new method to perform efficient independent component analysis (ICA) of random signals

Keywords

matrix algebra; neural nets; random processes; signal processing; unsupervised learning; abstract mechanical system; algorithms; blind source separation; digital signal processing; experimental results; independent component analysis; linear neural networks; orthonormal matrices; orthonormal signal processing; random signals; unsupervised neural learning rule; Digital signal processing; Independent component analysis; Mechanical systems; Neural networks; Power measurement; Signal analysis; Signal processing; Signal processing algorithms; Steady-state; Unsupervised learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on

Conference_Location

Munich

ISSN

1520-6149

Print_ISBN

0-8186-7919-0

Type

conf

DOI

10.1109/ICASSP.1997.595511

Filename

595511