The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 가중치(참조) 벡터의 메커니즘을 삭제하는 관점에서 두 가지 경쟁 학습 알고리즘을 설명합니다. 이 기술은 각각 분할 오류 및 왜곡 오류의 기준에 참여하는 적응성 삭제 및 민감도 삭제라고 합니다. 실험 결과는 평균 왜곡에서 제안된 접근법의 효율성을 보여줍니다.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
부
Michiharu MAEDA, Hiromi MIYAJIMA, "Competitive Learning Algorithms Founded on Adaptivity and Sensitivity Deletion Methods" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 12, pp. 2770-2774, December 2000, doi: .
Abstract: This paper describes two competitive learning algorithms from the viewpoint of deleting mechanisms of weight (reference) vectors. The techniques are termed the adaptivity and sensitivity deletions participated in the criteria of partition error and distortion error, respectively. Experimental results show the effectiveness of the proposed approaches in the average distortion.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_12_2770/_p
부
@ARTICLE{e83-a_12_2770,
author={Michiharu MAEDA, Hiromi MIYAJIMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Competitive Learning Algorithms Founded on Adaptivity and Sensitivity Deletion Methods},
year={2000},
volume={E83-A},
number={12},
pages={2770-2774},
abstract={This paper describes two competitive learning algorithms from the viewpoint of deleting mechanisms of weight (reference) vectors. The techniques are termed the adaptivity and sensitivity deletions participated in the criteria of partition error and distortion error, respectively. Experimental results show the effectiveness of the proposed approaches in the average distortion.},
keywords={},
doi={},
ISSN={},
month={December},}
부
TY - JOUR
TI - Competitive Learning Algorithms Founded on Adaptivity and Sensitivity Deletion Methods
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2770
EP - 2774
AU - Michiharu MAEDA
AU - Hiromi MIYAJIMA
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2000
AB - This paper describes two competitive learning algorithms from the viewpoint of deleting mechanisms of weight (reference) vectors. The techniques are termed the adaptivity and sensitivity deletions participated in the criteria of partition error and distortion error, respectively. Experimental results show the effectiveness of the proposed approaches in the average distortion.
ER -