Complexity reduction of singleton based neuro-fuzzy algorithm

被引：0

作者：

Baranyi, P ^{[1
]}

Lei, KF ^{[1
]}

Yam, Y ^{[1
]}

机构：

[1] Tech Univ Budapest, Hungarian Acad Sci, Mech Res Grp, H-1111 Budapest, Hungary

来源：

SMC 2000 CONFERENCE PROCEEDINGS: 2000 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOL 1-5 | 2000年

关键词：

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

During the past few years efficient singular value-based complexity reduction tools have been developed to fuzzy logic techniques. This paper introduces a singular value-based reduction method to the generalised type neural network. The method conducts singular value decomposition of the weighting functions defined on the connections among the neurons and generates certain linear combinations of the original weighting functions to form a new connection-net for the complexity reduced neural network.

引用

页码：2503 / 2508

页数：6

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