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

Woo, Wai Lok (2002) A new demixer scheme for blind source separation using general neural network model. In: Second International Conference on 3G Mobile Communication Technologies, 26th - 28th March 2001, London, UK.

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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.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	signal processing, neural net architecture, feedforward neural nets, feedback, convergence of numerical methods
Subjects:	G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Paul Burns
Date Deposited:	04 Jun 2019 08:39
Last Modified:	10 Oct 2019 18:33
URI:	http://nrl.northumbria.ac.uk/id/eprint/39464

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