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(Adaptive Structure of Modular Wavelet Neural Network Using Growing and Pruning Algorithm)  

Seo, Jae-Yong (Dept. of Information Technology Engineering, Korea University of Technology and Education)
Kim, Yong-Taek (Dept.of Electronics Electric Engineering, Chungang University)
Jo, Hyeon-Chan (Dept. of Information Technology Engineering, Korea University of Technology and Education)
Jeon, Hong-Tae (Dept.of Electronics Electric Engineering, Chungang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SC / v.39, no.1, 2002 , pp. 16-23 More about this Journal
Abstract
In this paper, we propose the growing and pruning algorithm to design the optimal structure of modular wavelet neural network(MWNN) with F-projection and geometric growing criterion. Geometric growing criterion consists of estimated error criterion considering local error and angle criterion which attempts to assign wavelet function that is nearly orthogonal to all other existing wavelet functions. These criteria provide a methodology which a network designer can construct MWNN according to one's intention. The proposed growing algorithm increases in number of module or the size of modules of MWNN. Also, the pruning algorithm eliminates unnecessary node of module or module from constructed MWNN to overcome the problem due to localized characteristic of wavelet neural network which is used to modules of MWNN. We apply the proposed constructing algorithm of the optimal structure of MWNN to approximation problems of 1-D function and 2-D function, and evaluate the effectiveness of the proposed algorithm.
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Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
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