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Learning process system for use with a neural network structure data processing apparatus

  • US 5,333,239 A
  • Filed: 01/11/1993
  • Issued: 07/26/1994
  • Est. Priority Date: 09/12/1988
  • Status: Expired due to Term
First Claim
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1. A learning process system for use with a neural network comprising an input layer including a first plurality of basic units, each including a basic unit input each connected to receive an input signal and a basic unit output each connected to receive a weight signal to be multiplied by the input signal received by the basic unit input, connected to provide a sum-of-products and connected to convert the sum-of-products by a threshold value function to provide a final result signal at a basic unit output, at least one intermediate layer including a second plurality of basic units, each including a basic unit input each connected to receive another input signal and a basic unit output each connected to receive the weight signal to be multiplied by the another input signal received by the basic unit input, connected to provide another sum-of-products and connected to convert the another sum-of-products by another threshold value function to provide another final result signal at the basic unit output, an output layer including at least one basic unit, each including a basic unit input each connected to receive a further input signal and a basic unit output each connected to receive the weight signal to be multiplied by the further input signal received by the basic unit input, connected to provide a further sum-of-products and connected to convert the further sum-of-products by a further threshold value function to provide a further final result signal at the basic unit output, and internal connections from the basic unit outputs of the input layer to the basic unit inputs of the at least one intermediate layer and from the basic unit outputs of the at least one intermediate layer to the basic unit inputs of the output layer, said learning process system comprising:

  • output signal providing means for, when a plurality of predetermined input signals are supplied to the input layer basic unit inputs, receiving first output signals from the basic unit output of each at least one basic unit of the output layer and for providing second output signals identical to the first output signals,error value means for receiving the second output signals and a teacher signal and for generating error signals designating an inconsistency between the second output signal and the teacher signal, andweight learning means for calculating and storing a weight updating signal in respective updating cycles and for generating the weight signal so that a sum of the error signals becomes within a predetermined allowable range by sequentially updating in updating cycles the weight signal in accordance with the weight updating signal based on the sum of the error signals determined at a first updating cycle, based on a once dalyed weight updating signal determined at a second updating cycle prior to the first updating cycle, and based on a twice delayed weight updating signal determined at a third updating cycle prior to the second updating cycle.

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