Conference paper
Separation of signals with overlapping spectra using signal characterisation and hyperspace filtering
Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373), pp.327-332
IEEE
The IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium AS-SPCC. (Lake Louise, Canada, 01/10/2000–04/10/2000)
2000
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.
Details
- Title
- Separation of signals with overlapping spectra using signal characterisation and hyperspace filtering
- Authors/Creators
- T. Jan (Author/Creator) - The University of MelbourneA. Zaknich (Author/Creator) - The University of Western AustraliaY. Attikiouzel (Author/Creator) - The University of Western Australia
- Publication Details
- Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373), pp.327-332
- Conference
- The IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium AS-SPCC. (Lake Louise, Canada, 01/10/2000–04/10/2000)
- Publisher
- IEEE
- Identifiers
- 991005540383607891
- Copyright
- © 2000 IEEE
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Conference paper
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