국가지식-학술정보
일정 학습계수와 이진 강화함수를 가진 자기 조직화 형상지도 신경회로망
Self-Organizing Feature Map with Constant Learning Rate and Binary Reinforcement
- 대한전자공학회
- Journal of the Korean Institute of Telematics and Electronics B
- Vol.32B No.1
-
1995.01180 - 188 (9 pages)
- 0
커버이미지 없음
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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