Predictive self-organizing neural network

Details Predictive self-organizing neural network Predictive self-organizing neural network

1991-01-31

1993-05-25

Boudreau, Leo H.

Image analysis

Histogram processing

For setting a threshold

382 14, 395 23, 395 24, G06K 962

Patent

active

052147150

ABSTRACT:
An A pattern recognition subsystem responds to an A feature representation input to select A-category-representation and predict a B-category-representation and its associated B feature representation input. During learning trials, a predicted B-category-representation is compared to that obtained through a B pattern recognition subsystem. With mismatch, a vigilance parameter of the A-pattern-recognition subsystem is increased to cause reset of the first-category-representation selection. Inputs to the pattern recognition subsystems may be preprocessed to complement code the inputs.

REFERENCES:
patent: 5054093 (1991-10-01), Cooper et al.
patent: 5058180 (1991-10-01), Khan
patent: 5060278 (1991-10-01), Fukemizu
patent: 5095443 (1992-03-01), Watanabe
Ryan, "The Resonance Correlation Network", IEEE Int'l Conf. on Neural Nets Jul. 1988.
"Art 3: Hierarchical Search Using Chemical Transmitters in Self-Organizing Pattern Recognition Architectures," Gail A. Carpenter et al., Neural Networks, in press, Mar. 1990.
Gail A. Carpenter, "Neural Network Models for Pattern Recognition and Associative Memory," Neural Networks, vol. 2, No. 4, 1989, New York, pp. 243-257.

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