Conference paper
Modified probabilistic neural network hardware implementation schemes
Proceedings of Digital Processing Applications (TENCON '96), Vol.1, pp.167-172
Proceedings of the 1996 IEEE Region 10 TENCON - Digital Signal Processing Applications Conference (Perth, Western Australia, 26/11/1996–29/11/1996)
1996
Abstract
The modified probabilistic neural network for nonlinear time series analysis was developed and introduced in 1991. It effectively represents a simple family of clustering methods for reducing the size of Specht's general regression neural network and retaining all its benefits. Three hardware implementation schemes for the most basic form of the modified probabilistic neural network are described. The first is an optoelectronic implementation and the other two are very large scale integration designs: a virtual implementation and a fully parallel implementation.
Details
- Title
- Modified probabilistic neural network hardware implementation schemes
- Authors/Creators
- A. Zaknich (Author/Creator)Y. Attikiouzel (Author/Creator)
- Publication Details
- Proceedings of Digital Processing Applications (TENCON '96), Vol.1, pp.167-172
- Conference
- Proceedings of the 1996 IEEE Region 10 TENCON - Digital Signal Processing Applications Conference (Perth, Western Australia, 26/11/1996–29/11/1996)
- Identifiers
- 991005541578807891
- Copyright
- © 1996 IEEE
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Conference paper
Metrics
151 File views/ downloads
73 Record Views