Analogue hardware and some convergence properties of the sources separation algorithm

Author

Achvar, Didier

Author_Institution

Lab. d´´Electron. d´´Autom. et de Inf., Ecole Nat. Super. des Tech. Ind. et des Mines d´´Ales, France

Volume

1

fYear

1993

fDate

25-29 Oct. 1993

Firstpage

883

Abstract

We present in our paper a simplified analogue hardware of the two-neuron Herault-Jutten network (1989, 1991) for separation of two sources from a linear and instantaneous mixture. The simplification is in the choice of the nonlinear functions used by the learning rule. Based on theoretical considerations and simulation results, the influence of these nonlinearities and the statistical nature of sources on the convergence of the algorithm are pointed out. In order to determine the properties and the limitations of our analogue hardware, the behavior of the algorithm is derived finally for strong nonlinear functions, as they are actually implemented in our circuit.

Keywords

analogue integrated circuits; convergence; neural nets; signal processing; analogue hardware; convergence properties; linear instantaneous mixture; nonlinearities; sources separation algorithm; strong nonlinear functions; two-neuron network; Circuits; Convergence; Convolution; Filters; Hardware; Linearity; Microphones; Production; Signal processing algorithms; Source separation;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on

Print_ISBN

0-7803-1421-2

Type

conf

DOI

10.1109/IJCNN.1993.714052

Filename

714052