Hardware-oriented algorithm for associative memories on cellular neural networks

Abstract

We present a new learning algorithm used to implement associative memories on digital cellular neural networks. The algorithm can be easily implemented in hardware or simulated on a digital computer without numerical errors. These attractive features come from the finite precision of connection weights, automatically taken into account as a design constraint; moreover, no multiplication is needed for weight computation.