Integrated Image Associative Memory and Its Optical Implementation

We present the concept of integrated processing to combine intuitive processing of neural networks with logical processing of the conventional digital computer. We investigate a way to embody the concept in the neural network system by introducing external constraints in terms of external input. The effect of the external input is analyzed using the generalized projection method. The concept of integrated processing is applied to an image associative memory system, and the system is optically implemented for high-speed parallel processing incorporating it with the computer. The experimental result is presented to illustrate the effectiveness of the external input to control the output of the image associative memory.