Self-Organizing Feature Map with Constant Learning Rate and Binary Reinforcement

일정 학습계수와 이진 강화함수를 가진 자기 조직화 형상지도 신경회로망

  • 조성원 (홍익대학교 전기제어공학과) ;
  • 석진욱 (홍익대학교 전기제어공학과)
  • Published : 1995.01.01

Abstract

A modified Kohonen's self-organizing feature map (SOFM) algorithm which has binary reinforcement function and a constant learning rate is proposed. In contrast to the time-varing adaptaion gain of the original Kohonen's SOFM algorithm, the proposed algorithm uses a constant adaptation gain, and adds a binary reinforcement function in order to compensate for the lowered learning ability of SOFM due to the constant learning rate. Since the proposed algorithm does not have the complicated multiplication, it's digital hardware implementation is much easier than that of the original SOFM.

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