Neural network with normalized learning constant for high-speed

Details Neural network with normalized learning constant for high-speed Neural network with normalized learning constant for high-speed

1989-09-13

1992-03-03

MacDonald, Allen R.

G06F 1518

Patent

active

050938991

ABSTRACT:
The present invention is concerned with a signal processing system having a learning function pursuant to the back-propagation learning rule by the neural network, in which the learning rate is dynamically changed as a function of input values to effect high-speed stable learning. The signal processing system of the present invention is so arranged that, by executing signal processing for the input signals by the recurrent network formed by units each corresponding to a neuron, the features of the sequential time series pattern such as voice signals fluctuating on the time axis can be extracted through learning the coupling state of the recurrent network. The present invention modifies the prior art weight change algorithm .DELTA.W.sub.ji(n+1) =.eta...delta..sub.pi.+.alpha..W.sub.ji(n) into .DELTA.W.sub.ji(n+1) =.eta...beta.(.alpha..sub.pj O.sub.pi)+.alpha..W.sub.ji(n) where .beta..sub.j =1/(.SIGMA..sub.i O.sub.pi.sup.2 +1) is used to normalize the learning constant.

REFERENCES:
Implementation of Neural Networks for Speech Recognition on a Transputer Array; Chong et al.; Cambridge University; Mar. 10, 1988.
Successfully Using Peak Learning Rates of 10 (and Greater) in Backpropagation Networks with the Heuristic Learning Algorithm; John P. Cater; IEEE First International Conference on Neural Networks; 21-24 Jun. 1987; vol. 2; pp. 645-651.
M. F. Tenorio et al.: "Adaptive Networks as a Model for Human Speech Development", Jul. 1988, vol. II, pp. 235-242.
F. E. Norrod et al.: "Feedback-Induced Sequentiality in Neural Networks", Jun. 1987, vol. II, pp. 251-258.
D. E. Rumelhart et al.: "Parallel Distributed Processing", vol. 1: Foundations, 1986, pp. 318-362.
B. Macukow et al.: "Neural Network Model Using a Normalized Inner Product as a Measure of Similarity", Jul. 1988, pp. 225-230.

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