A linear ridgelet network approach for fault diagnosis of analog circuit

被引:15
|
作者
Xiao YingQun [1 ]
He YiGang [1 ]
机构
[1] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
fault diagnosis of analog circuit; ridgelet; linear ridgelet network; wavelet packet decomposition; NEURAL-NETWORK; REPRESENTATION; TRANSFORM;
D O I
10.1007/s11432-010-4077-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A linear ridgelet network combining ridgelet, linear term and the standard feed-forward neural network used for diagnosing the faults of analog circuit is constructed, and a training algorithm based on the steepest gradient descent method and momentum method for this network and the procedure for diagnosing these faults are proposed. The resulting linear ridgelet network can learn more rapidly from training samples and handle more effectively the complicated fault information of circuit under test than wavelet network and ridgelet network, classifying these faults efficiently and correctly and achieving a high classification accuracy. The simulation results demonstrate the effectiveness of this approach.
引用
收藏
页码:2251 / 2264
页数:14
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