Abstract
The author presents a mathematical framework for the design of neural networks as associative memories or as pattern classifiers. This framework takes into account the characteristics and the limitations of the electrical components which are the building blocks for the proposed devices. He also presents conditions that given vectors must satisfy to successfully store them in the network. The conditions suggest a preprocessing procedure of the desired memories to render them storable.

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