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A neural network, which can be implemented either in hardware or software, is constructed of neurons or neuron circuits each having only one significant processing element in the form of a multiplier. The number of training examples is compared to the number of neurons in the neural network to effec

A neural network, which can be implemented either in hardware or software, is constructed of neurons or neuron circuits each having only one significant processing element in the form of a multiplier. The number of training examples is compared to the number of neurons in the neural network to effectuate training. The neural network utilizes a training algorithm which does not require repetitive training and which yields a global minimum to each given set of input vectors.

대표청구항 ▼

[ What is claimed is:] [1.] A method for training a neural network comprising a plurality of neurons, said method for calculating weight values, said method comprising the following steps:(a) providing a plurality of training examples;(b) comparing the number of said training examples with the numbe

[ What is claimed is:] [1.] A method for training a neural network comprising a plurality of neurons, said method for calculating weight values, said method comprising the following steps:(a) providing a plurality of training examples;(b) comparing the number of said training examples with the number of neurons in said neural network;(c) providing at least two techniques for calculating said weight values, wherein(i) if the number of neurons is equal to the number of training examples, using a matrix-inversion technique to solve for the value of each weight;(ii) if the number of neurons is not equal to the number of training examples, using a least-squares estimation technique to solve for the value of each weight.