Photonic implementation of Hopfield neural network for associative pattern recognition

被引：2

作者：

Munshi, S ^{[1
]}

Bhattacharyya, S ^{[1
]}

Datta, AK ^{[1
]}

机构：

[1] Univ Calcutta, Dept Appl Phys, Kolkata 700009, W Bengal, India

来源：

PHOTONICS 2000: INTERNATIONAL CONFERENCE ON FIBER OPTICS AND PHOTONICS | 2001年 / 4417卷

关键词：

Hopfield network; artificial neural network; optical neural network; training matrix; matrix-vector multiplication;

D O I：

10.1117/12.441352

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

An optical matrix-vector multiplier has been 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.

引用

页码：558 / 562

页数：5

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