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

W. L. Woo, S. Sali

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

There has been a surge of interest in blind source separation (BSS) because of its potential applications in several areas of engineering and science such as wireless systems. We propose a new neural network demixing scheme using a general neural network structure for the BSS problem for the instantaneous mixtures. It is shown that the existing feedforward (FF) and feedback (FB) neural network schemes can be reduced from the new general model. The results demonstrate that the new scheme is more robust and offers superior convergence properties.
Original languageEnglish
Pages383-386
Number of pages4
DOIs
Publication statusPublished - 7 Aug 2002
EventSecond International Conference on 3G Mobile Communication Technologies - IEE London, London, United Kingdom
Duration: 26 Mar 200128 Mar 2001
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=923494

Conference

ConferenceSecond International Conference on 3G Mobile Communication Technologies
CountryUnited Kingdom
CityLondon
Period26/03/0128/03/01
Internet address

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