Holographic implementation of a fully connected neural network

A holographic implementation of a fully connected neural network is presented. This model has a simple structure and is relatively easy to implement, and its operating principles and characteristics can be extended to other types of networks, since any architecture can be considered as a fully connected network with some of its connections missing. The basic principles of the fully connected network are reviewed. The optical implementation of the network is presented. Experimental results which demonstrate its ability to recognize stored images are given, and its performance and analysis are discussed based on a proposed model for the system. Special attention is focused on the dynamics of the feedback loop and the tradeoff between distortion tolerance and image-recognition capability of the associative memory.<>