Neural network training using the bimodal optical computer

Mustafa A. G. Abushagur; Anwar M. Helaly; H. John Caulfield

doi:10.1117/12.21158

1 August 1990 Neural network training using the bimodal optical computer

Mustafa A. G. Abushagur, Anwar M. Helaly, H. John Caulfield

Proceedings Volume 1294, Applications of Artificial Neural Networks; (1990) https://doi.org/10.1117/12.21158
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

Using the bimodal optical computer for training a hetroassociative memory of a neural network is introduced. The storage capacity of the trained hetroassociative memory is shown to be much higher than that for the Hopefield model. A comparison with the pseudoinverse model shows that in the proposed method the vector recall accuracy is higher when the number of vectors is greater than their size. This method has the potential of being faster than the other methods because of its parallel processing nature. I.

Citation Download Citation

Mustafa A. G. Abushagur, Anwar M. Helaly, and H. John Caulfield "Neural network training using the bimodal optical computer", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21158

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