Neural network training using the bimodal optical computer
Mustafa A. G. Abushagur, Anwar M. Helaly, H. John Caulfield · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
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.