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An analog implementation of a neuron using standard VLSI components is described. The node is capable of both delta-rule and simple error-correcting learning. Decomposition into functional blocks allows the parts of the design to be easily separated and understood. The connectivity problem is eased by serially encoding inputs so that all nodes in a layer are connected to a single line carrying activations...
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