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Mechanical systems and signal processing v.103, 2018년, pp.368 - 380   SCIE
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Component isolation for multi-component signal analysis using a non-parametric gaussian latent feature model

Yang, Yang (Department of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China ) ; Peng, Zhike (Department of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China ) ; Dong, Xingjian (Department of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China ) ; Zhang, Wenming (Department of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China ) ; Clifton, David A. (Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK ) ;
  • 초록  

    Abstract A challenge in analysing non-stationary multi-component signals is to isolate nonlinearly time-varying signals especially when they are overlapped in time and frequency plane. In this paper, a framework integrating time-frequency analysis-based demodulation and a non-parametric Gaussian latent feature model is proposed to isolate and recover components of such signals. The former aims to remove high-order frequency modulation (FM) such that the latter is able to infer demodulated components while simultaneously discovering the number of the target components. The proposed method is effective in isolating multiple components that have the same FM behavior. In addition, the results show that the proposed method is superior to generalised demodulation with singular-value decomposition-based method, parametric time-frequency analysis with filter-based method and empirical model decomposition base method, in recovering the amplitude and phase of superimposed components. Highlights The approach integrates non-parametric latent feature model and TFA-based demodulation. The approach can infer the components automatically without defining the number of components. The approach can accurately recover the amplitudes of superimposed components at the cross points.


  • 주제어

    Time-frequency analysis .   Non-parametric latent feature model .   Time series .   Continuous phase modulation .   Component extraction.  

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