Mask controled neural networks

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382 16, 364200, 3642766, G06K 900

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050142194

ABSTRACT:
A mask neutral network for processing that allows an external source of control to continuously direct state transition of the neural network toward selected states and away from other states. The network, through externally controlled masking, can focus attention on selected attributes of observed data, solutions or results. The masking is appliciable across three major categories of networks in that it facilitates augmented recall, directed learning and constrained optimization.

REFERENCES:
patent: 4641351 (1987-02-01), Preston, Jr.
patent: 4803736 (1989-02-01), Grossberg et al.
M. A. Cohen & S. Grossberg, "Masking Fields: A Massively, Parallel Neural Architecture for Learning, Recognizing, and Predicting Multiple Groupings of Pattern Data," Appl. Opt., vol. 26, No. 10, pp. 1866-1891 (May 15, 1987).
G. Macukow & H. H. Arsenault, "Optical Associative Memory Model Based on Neural Networks having Variable Interconnection Weights," Appl. Opt., vol. 26, No. 5, pp. 924-928 (Mar. 1, 1987).
A. Kuh & B. W. Dickinson, "Informnation Capacity of Modified Associative Memory Models," 1986 IEEE International Symposium on Information Theory, Ann Arbor, MI (Oct. 6-10, 1986).
G. E. Hinton, "Learning in Massively Parallel Nets," Proceedings AAAI-86: Fifth National Conference on Artificial Intelligence, Univ. of Penn., Philadelphia, Pa. (Aug. 11-15, 1986).
L. Bobrowski & E. R. Caianiello, "Comparison of Two Unsupervised Learning Algorithms," Biol. Cybern. (Germany), vol. 37, No. 1, pp. 1-7 (1980).

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