A Neural Network for Concept Learning : Recognitron

개념 학습에 의한 신경 회로망 컴퓨터

  • 이기한 (서울대학교 컴퓨터 공학과) ;
  • 황희융 (서울대학교 컴퓨터 공학과) ;
  • 김춘석 (숭실대학교 전기공학과)
  • Published : 1989.07.21

Abstract

Concept is the set of selected neurons in a stable state of a neurel network. The Recognitron uses a parallel feedback structure to support concept learning. A number of clusters can exist in response to a given input, each of which make up a selective neuron. There are supervised and unsupervised learnig methods in concept teaming. In this paper, we have chosen unsupervised learning. Also, a new concept called relaxational learning has been introduced to stop runaway weights

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