Silicon retina: image compression by associative neural network based on code and graph theories

An associative neural network (NN) is constructed on the basis of code and graph theories to realize a silicon retina. Each neuron is an EXCLUSIVE-OR unit in the digital NN (DNN) based on finite field GF(2). Each neuron is an adder unit in the analog NN (ANN) based on real field R/sup b/. The network has the following features: no multiplier, sparsity, cellular structure, high concurrency, and high speed. The DNN and the ANN can be applied to data compression for binary and analog images, respectively. The S/N rate in the reproduction image depends on the network structure. Secret image communication and image recognition are possible.<
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