Results on AR-modelling of nonstationary signals
Signal Processing
Ten lectures on wavelets
New cumulant-based approaches for non-Gaussian time-varying AR models
Signal Processing
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This paper focuses on the modeling of non-Gaussian autoregressive (AR) model for a wide range of physical signals. A practical algorithm based on higher-order cumulants is proposed to deal with the problem of estimating the non-Gaussian AR model with transient coefficients. Wavelet basis is used to identify the transient coefficients. The performance in terms of Haar and Morlet basis is evaluated with non-stationary processes. The experimental results show the flexibility of capturing the local events by using the presented model.