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Algorithm for optimizing bipolar interconnection weights with applications in associative memories and multitarget classification
- Source :
- Applied Optics; August 1999, Vol. 38 Issue: 23 p5032-5038, 7p
- Publication Year :
- 1999
-
Abstract
- An algorithm for optimizing a bipolar interconnection weight matrix with the Hopfield network is proposed. The effectiveness of this algorithm is demonstrated by computer simulation and optical implementation. In the optical implementation of the neural network the interconnection weights are biased to yield a nonnegative weight matrix. Moreover, a threshold subchannel is added so that the system can realize, in real time, the bipolar weighted summation in a single channel. Preliminary experimental results obtained from the applications in associative memories and multitarget classification with rotation invariance are shown.
Details
- Language :
- English
- ISSN :
- 1559128X and 21553165
- Volume :
- 38
- Issue :
- 23
- Database :
- Supplemental Index
- Journal :
- Applied Optics
- Publication Type :
- Periodical
- Accession number :
- ejs37380893