Photonic implementation of Hopfield neural network for associative pattern recognition

Soumika Munshi; Siddhartha Bhattacharyya; Asit K. Datta

doi:10.1117/12.441352

25 September 2001 Photonic implementation of Hopfield neural network for associative pattern recognition

Soumika Munshi, Siddhartha Bhattacharyya, Asit K. Datta

Proceedings Volume 4417, Photonics 2000: International Conference on Fiber Optics and Photonics; (2001) https://doi.org/10.1117/12.441352
Event: Photonics 2000: International Conference on Fiber Optics and Photonics, 2001, Calcutta, India

Abstract

An optical matrix-vector multiplier has ben efficiently used for photonic implementation of Hopfield network model, which is used for binary pattern recognition. Training matrices are recorded on electrically addressed spatial light modulator, where each matrix is composed of the same row of each pattern, that the network is being trained with. After training, if an unknown pattern is presented to the network in the form of a vector, the output vector is obtained by the element that has the highest magnitude through a winner- take-all algorithm. Pattern can be recognized even if the input is noisy and distorted.

Citation Download Citation

Soumika Munshi, Siddhartha Bhattacharyya, and Asit K. Datta "Photonic implementation of Hopfield neural network for associative pattern recognition", Proc. SPIE 4417, Photonics 2000: International Conference on Fiber Optics and Photonics, (25 September 2001); https://doi.org/10.1117/12.441352

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