期刊名称：Neural Information Processing: Letters and Reviews
电子版ISSN：1738-2532
出版年度：2007
卷号：11
期号：9
页码：195-202
出版社：Neural Information Processing
摘要：The self-organizing relationship (SOR) network was proposed in order to extract a desirable input-output relationship
of a target system by using learning vectors with their evaluations. In the execution mode, the SOR network can be
used as a fuzzy inference engine. The output of the SOR network depends on matching parameters which correspond
to the standard deviation of the Gaussian membership function as used in fuzzy inference. However, the issue of the
optimization of the matching parameters has not yet been treated in previous works. In this paper we propose a method
to optimize matching parameters of the SOR network. Energy functions are introduced to the SOR network in order to
tune the matching parameter with a gradient descent method. The proposed method is verified through a function
approximation problem.
关键词：Self-organizing relationship network, matching parameter, energy function, tuning mode
