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Method of and system for controlling learning in neural network

  • US 5,313,559 A
  • Filed: 02/10/1992
  • Issued: 05/17/1994
  • Est. Priority Date: 02/15/1991
  • Status: Expired due to Fees
First Claim
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1. A method of managing learning in a neural network, comprising the steps of:

  • providing reference data representing criteria of protraction of the learning;

    performing learning on a current problem by use of learning pattern data for learning cycles in accordance with a predetermined learning method while generating and updating evaluation data representing a learning state of the neural network for each learning cycle;

    comparing the evaluation data with the reference data for each learning cycle;

    judging in accordance with the compared result and predetermined judging conditions whether or not there exists a possibility of protraction of the learning;

    displaying, when it is judged that there exists the possibility of the learning protraction, a list of learning methods for a user;

    selectively displaying past evaluation data for each of past problems which is analogous to the current problem, a past learning data set for each of the past problems, and a learning method for each of the past problems employed when it was judged that there existed a possibility of learning protraction in the learning of each of the past problems;

    selecting a new learning method from the list by a user based on the displayed past evaluation data, past learning data set and learning method, for each of the past problems, respectively; and

    re-initiating the learning in accordance with the new learning method selected by a user.

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