Fault Pattern Recognition Based on Improved Wavelet Neural Network

被引：0
|
作者：
Feng, Deng-Chao [1 ]
Yang, Zhao-Xuan [1 ]
Wang, Zeng-Min [1 ]
机构：
[1] Tianjin Univ, Inst Elect & Informat Engn, Tianjin 300072, Peoples R China
来源：
ADVANCES IN COGNITIVE NEURODYNAMICS, PROCEEDINGS | 2008年
关键词：
D O I：
10.1007/978-1-4020-8387-7_178
中图分类号：
Q189 [神经科学];
学科分类号：
071006 ;
摘要：
The basic principle of wavelet neural network is analyzed and the learning algorithm is improved as well. Correspondingly, fault pattern recognition model is constructed based on improved wavelet neural network. Simulation experiment shows that improved wavelet neural network has good fault-tolerant capacity and global convergence. However, how to establish an objective criterion of parameter settings and enhance the real time capability of fault pattern recognition still need further research.
引用
收藏
页码：1039 / +
页数：3
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