DocumentCode :
3389793
Title :
Study on effective state monitoring of analog circuit based on HMM
Author :
Xu, Lijia ; Long, Bing ; Wang, Houjun ; Jiang, Jianheng
Author_Institution :
Univ. of Electron. Sci. & Technol. of China, Chengdu
fYear :
2008
fDate :
10-12 Oct. 2008
Firstpage :
344
Lastpage :
348
Abstract :
Feature extraction is the most important step in effective state monitoring of analog circuit. Due to variety of features, the paper proposes a new approach to monitor state of analog circuit: Firstly, composite features including time-domain features and wavelet features are extracted from the response signal through giving different stimulus to analog circuit; Secondly, HMMs trained by composite features are utilized to recognize different faults, thus we can acquire effective state monitoring of analog circuit. The proposed approach is applied to a typical analog circuit and experimental results show that the proposed approach provides a better monitoring ability by comparing with BP network and offers a practical method for state monitoring of analog circuit.
Keywords :
analogue circuits; feature extraction; hidden Markov models; monitoring; time-domain analysis; wavelet transforms; HMM; analog circuit; feature extraction; hidden Markov model; state monitoring; time-domain features; wavelet features; Analog circuits; Circuit testing; Condition monitoring; Feature extraction; Hidden Markov models; Parametric statistics; Pattern recognition; Probability; Stochastic processes; Time domain analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Simulation and Scientific Computing, 2008. ICSC 2008. Asia Simulation Conference - 7th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1786-5
Electronic_ISBN :
978-1-4244-1787-2
Type :
conf
DOI :
10.1109/ASC-ICSC.2008.4675382
Filename :
4675382
Link To Document :
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