Neural network apparatus

Details Neural network apparatus Neural network apparatus

1991-04-15

1994-02-01

Boudreau, Leo H.

Image analysis

Histogram processing

For setting a threshold

G06K 900

Patent

active

052838382

ABSTRACT:
When performing learning for a neural network, a plurality of learning vectors which belong to an arbitrary category are used, and self-organization learning in the category is carried out. As a result, the plurality of learning vectors which belong to the category are automatically clustered, and the contents of weight vectors in the neural network are set to representative vectors which exhibit common features of the learning vectors of each cluster. Then, teacher-supervised learning is carried out for the neural network, using the thus set contents of the weight vectors as initial values thereof. In the learning process, an initial value of each weight vector is set to the representative vector of each cluster obtained by clustering. Therefore, the number of calculations required until the teacher-supervised learning is converged is greatly reduced.

REFERENCES:
patent: 4479241 (1984-10-01), Buckley
patent: 5048100 (1991-09-01), Kuperstein
patent: 5063601 (1991-11-01), Hayduk
Lippmann, "An Introduction to Computing with Neural Nets", IEEE ASSP Magazine, Apr. 1987, pp. 4-22.

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