Optimization apparatus

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395 24, G06F 1518, G06F 1516

Patent

active

052533271

ABSTRACT:
An optimization apparatus using a layered neural network having an input layer formed of input units and supplied with input data and an output layer formed of output units connected to the individual input units with specified synaptic weights, which comprises a calculator circuit for calculating, for each output unit, the degree of similarity between the input data and the synaptic weight as well as the evaluation function value by causing the optimization problem to correspond to the fired units in the output layer, a detector for detecting the best matching optimum output unit on the basis of the output of the calculator circuit, and a self-organization circuit for changing the synaptic weights of a group of the output units associated with the optimum unit detected by the detector.

REFERENCES:
patent: 4660166 (1987-04-01), Hopfield
patent: 4862406 (1989-08-01), Fisher
patent: 4979124 (1990-12-01), Sachse et al.
Kazmierczak et al., "Adaptive Systems in Pattern Recognition," IEEE Trans. Electronic Computers, Dec. 1963, 822-835.
Steinbuch et al., "Learning Matrices and Their Applications", IEEE Trans. Electronic Computers, Dec. 1963, 846-862.
Nasrabadi et al., "Vector Quantization of Images Based Upon the Kohonen Self-Organizing Feature Maps", IEEE Intl. Conf. on Neural Networks, Jul. 1988, I-101-I-108.
Moopenn et al., "A Neural Network for Euclidean Distance Minimization", IEEE Intl. Conf. on Neural Networks, Jul. 1988, II-349-II-356.

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