Separation of signals with overlapping spectra using signal characterisation and hyperspace filtering

T. Jan, A. Zaknich, Y. Attikiouzel

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

Abstract

For separation of signals with overlapping spectra. Classical linear filters fail to perform effectively. Nonlinear filters such as Volterra filters or artificial neural networks (ANNs) can perform better but their implementations are often impractical due to their computational complexity. In this paper an ANN based hyperspace signal modeling is used to separate signals with overlapping spectra. The computational complexity of the ANN is reduced significantly by a simple feature extraction utilizing the unique temporal characteristics of the signals. The results show that difficult signal separation and filtering can be achieved efficiently by employing an ANN and an effective feature extraction.

Original languageEnglish
Title of host publicationIEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages327-332
Number of pages6
ISBN (Electronic)0780358007, 9780780358003
DOIs
Publication statusPublished - 2000
Externally publishedYes
EventIEEE Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000 - Lake Louise, Canada
Duration: 1 Oct 20004 Oct 2000

Publication series

NameIEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000

Conference

ConferenceIEEE Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000
Country/TerritoryCanada
CityLake Louise
Period1/10/004/10/00

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