A self creating and organizing neural network

자기 분열 및 구조화 신경 회로망

  • 최두일 (연세대학교 전기공학과) ;
  • 박상희 (연세대학교 전기공학과)
  • Published : 1991.10.01

Abstract

The Self Creating and organizing (SCO) is a new architecture and one of the unsupervized learning algorithm for the artificial neural network. SCO begins with only one output node which has a sufficiently wide response range, and the response ranges of all the nodes decrease with time. Self Creating and Organizing Neural Network (SCONN) decides automatically whether adapting the weights of existing node or creating a new node. It is compared to the Kohonen's Self Organizing Feature Map (SOFM). The results show that SCONN has lots of advantages over other competitive learning architecture.

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