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Fuzzy Entropy Based Combined Learning Algorithm for Neural Networks 被引量:3

Fuzzy Entropy Based Combined Learning Algorithm for Neural Networks
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摘要 Learning is one of key problems of artificial neural networks. In this paper, we present a kind of combined learning algorithm based on fuzzy entropy criterion for neural networks. The basic idea is to simulate the learning mechanism of human brain and overcome the limitations of monocrifsterion learning. The comparison is made between the given learning algorithm and the typical BP algorithm in order to show the characteristics of the new algorithm. Learning is one of key problems of artificial neural networks. In this paper, we present a kind of combined learning algorithm based on fuzzy entropy criterion for neural networks. The basic idea is to simulate the learning mechanism of human brain and overcome the limitations of monocrifsterion learning. The comparison is made between the given learning algorithm and the typical BP algorithm in order to show the characteristics of the new algorithm.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 1996年第1期15-22,共8页 系统工程与电子技术(英文版)
关键词 Artificial neural networks Combined learning Fuzzy entropy criterion. Artificial neural networks, Combined learning, Fuzzy entropy criterion.
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