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Proceedings Paper

Photonic implementation of Hopfield neural network for associative pattern recognition
Author(s): Soumika Munshi; Siddhartha Bhattacharyya; Asit K. Datta
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Paper 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.

Paper Details

Date Published: 25 September 2001
PDF: 5 pages
Proc. SPIE 4417, Photonics 2000: International Conference on Fiber Optics and Photonics, (25 September 2001); doi: 10.1117/12.441352
Show Author Affiliations
Soumika Munshi, Univ. of Calcutta (India)
Siddhartha Bhattacharyya, Univ. of Calcutta (India)
Asit K. Datta, Univ. of Calcutta (India)

Published in SPIE Proceedings Vol. 4417:
Photonics 2000: International Conference on Fiber Optics and Photonics
S. K. Lahiri; Ranjan Gangopadhyay; Asit K. Datta; Samit K. Ray; B. K. Mathur; S. Das, Editor(s)

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