A new demixer scheme for blind source separation using general neural network model

W. L. Woo, S. Sali

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

A new demixer scheme for blind source separation from instantaneous mixtures has been presented using a general neural network model. It is proven that the existing neural network demixer schemes used for blind source separation can be classed as simpler versions of the new model. Computer simulations are presented to demonstrate that the new scheme is more robust and faster to converge than the existing schemes.

Original languageEnglish
Title of host publication6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis
PublisherIEEE
Pages379-381
Number of pages3
Volume2
ISBN (Print)0780367030
DOIs
Publication statusPublished - 7 Aug 2002
Event6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Kuala Lumpur, Malaysia
Duration: 13 Aug 200116 Aug 2001

Conference

Conference6th International Symposium on Signal Processing and Its Applications, ISSPA 2001
CountryMalaysia
CityKuala Lumpur
Period13/08/0116/08/01

Fingerprint

Dive into the research topics of 'A new demixer scheme for blind source separation using general neural network model'. Together they form a unique fingerprint.

Cite this