Model of adaptive neural network for pattern recognition

Eugene I. Shubnikov

doi:10.1117/12.195596

7 December 1994 Model of adaptive neural network for pattern recognition

Eugene I. Shubnikov

Proceedings Volume 2430, Optical Memory & Neural Networks '94: Optical Neural Networks; (1994) https://doi.org/10.1117/12.195596
Event: Optical Memory and Neural Networks: International Conference, 1994, Moscow, Russian Federation

Abstract

A three-layered neural network (NN) for pattern recognition with feedback and complex states of neurons and interconnections is suggested. NN is based on adaptive resonance principles and consists of comparison, recognition and selective attention (vigilance) layers. Comparison is carried out in spectral domain, recognition and selective attention -- in image space. Parallel-sequential accessing to long-term memory is used. Adaptation is realized by creation of new recognition categories and by long-term memory variance when the input pattern is similar enough. Hybrid opto-electronic implementation of NN is used. The main optical part is a joint transform correlator with a dynamic holographic filter.

Citation Download Citation

Eugene I. Shubnikov "Model of adaptive neural network for pattern recognition", Proc. SPIE 2430, Optical Memory & Neural Networks '94: Optical Neural Networks, (7 December 1994); https://doi.org/10.1117/12.195596

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