Structure optimization of wavelet neural network using rough set theory

被引：0

作者：

Li, YG ^{[1
]}

Shen, J ^{[1
]}

Lu, ZC ^{[1
]}

机构：

[1] SE Univ, Dept Power Engn, Nanjing 210096, Peoples R China

来源：

PROCEEDINGS OF THE 4TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-4 | 2002年

关键词：

rough sets; wavelet neural network; wavelet frame; dependency of attributes;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents an approach to minimize the redundancy of structure existing in wavelet neural networks based on frame using rough sets theory. The original structure of wavelet network is obtained through time-frequency analysis. Then the redundant nodes are eliminated in light of dependecy between the output of the network and-the nodes in the hidden layers to optimize the structure of wavelet network. Simulation results illustrate the proposed method is simple and effective.

引用

页码：652 / 655

页数：4

共 6 条

[1] THE WAVELET TRANSFORM, TIME-FREQUENCY LOCALIZATION AND SIGNAL ANALYSIS
DAUBECHIES, I
[J]. IEEE TRANSACTIONS ON INFORMATION THEORY, 1990, 36 (05) : 961 - 1005
[2] Fuzzy wavelet networks for function learning
Ho, DWC
Zhang, PA
Xu, JH
[J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2001, 9 (01) : 200 - 211
[3] Huang Dexian, 1999, Journal of Tsinghua University (Science and Technology), V39, P91
[4] PAWLAK Z, 1996, IEEE INT C SYST, P738
[5] WAVELET NETWORKS
ZHANG, QG
BENVENISTE, A
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1992, 3 (06): : 889 - 898
[6] Zhang QH, 1997, IEEE T NEURAL NETWOR, V8, P227, DOI 10.1109/72.557660

← 1 →