• 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