Fourier optical realization of cellular neural networks

Cellular neural networks (CNNs) consist of analog, nonlinear, dynamic processing elements which are locally interconnected. Most applications in the areas of image processing, pattern recognition and robot control require interconnections between all elements which are space invariant. This suggests an optical CNN implementation because optical processors are perfectly suited for both space invariant signal processing and complete interconnections between all elements. The theoretical and practical aspects of a hardware realization are described. The results of an optical CNN performing feature extraction are presented