摘要
从竞争学习的角度提出模糊C 均值算法中隶属度的新解释 ,并基于隶属度的新解释提出对手抑制式模糊C 均值算法 .理论分析和实验表明 :对手抑制式模糊C 均值算法提高了模糊C
A new interpretation of the membership degree of the fuzzy C-means algorithm is presented on the basis of competitive learning and then a new algorithm called rival checked fuzzy C-means algorithm is developed.The theoretical analysis and experimental results show that the new algorithm improves the convergence speed of the fuzzy C-means algorithm.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2000年第7期63-66,共4页
Acta Electronica Sinica
基金
国家自然科学基金!(No.69472 0 4 6)
关键词
模糊C-均值算法
隶属度
竞争学习
fuzzy C-means algorithm
membership degree
competitive learning
