Discrete-time domain poles zeros identification using back propagation neural networks

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)22_Publication in policy or professional journal

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)215-218
Journal / PublicationIEE Conference Publication
Publication statusPublished - 1991

Conference

Title6th International Conference on Digital Processing of Signals in Communications
PlaceUnited Kingdom
CityLoughborough
Period2 - 6 September 1991

Abstract

This paper describes a back propagation neural network applying to poles zeros identification in discrete time domain. Traditional Recursive Least Squares (RLS) algorithm is time consuming and sensitive to noise. Neural networks possess massive parallel processing capability and noise immunity, the time and noise constraints can be eliminated. The results are encouraging and demonstrate that neural networks offer new promising directions towards solving system identification problems radically.