DocumentCode
2025383
Title
Structure optimization of wavelet neural network using rough set theory
Author
Li, Yiguo ; Shen, Jiong ; Lu, Zhenzhong
Author_Institution
Dept. of Power Eng., Southeast Univ., Nanjing, China
Volume
1
fYear
2002
fDate
2002
Firstpage
652
Abstract
This paper presents an approach to minimize the redundancy of structure existing in frame-based wavelet neural networks using the rough sets theory. The original structure of the wavelet network is obtained through a time-frequency analysis. Then the redundant nodes are eliminated in light of the dependency between the output of the network and nodes in the hidden layers to optimize the structure of the wavelet network. Simulation results show the proposed method is simple and effective.
Keywords
neural nets; optimisation; rough set theory; time-frequency analysis; wavelet transforms; attribute dependency; redundant nodes; rough set theory; structure optimization; time-frequency analysis; wavelet frame; wavelet neural network; Automation; Intelligent control; Neural networks; Power engineering; Rough sets; Set theory; Time frequency analysis; Wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN
0-7803-7268-9
Type
conf
DOI
10.1109/WCICA.2002.1022193
Filename
1022193
Link To Document