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Evolution and learning in neural networks: the number and distribution of learning trials affect the rate of evolution

  • US 5,245,696 A
  • Filed: 11/21/1990
  • Issued: 09/14/1993
  • Est. Priority Date: 11/21/1990
  • Status: Expired due to Fees
First Claim
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1. In a neural network system for use in application tasks including optical character recognition techniques, an evolutionary evaluation and learning method comprising the steps of:

  • forming plural genetic representations of an application task including recognizing a plurality of characters where each character has a bit configuration specifying initial connection strengths between filter lays and category units,converting said plural genetic representations to neural networks,assigning to each network i, k(i) learning trails, chosen randomly between zero and 2K, andtraining each neural network to optimally perform the application task including optical character recognition where the number of learning trials per network is randomly chosen.

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