
Proceedings Paper
Photonic implementation of Hopfield neural network for associative pattern recognitionFormat | Member Price | Non-Member Price |
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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
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)
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
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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