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Time series analysis in the frequency domain

Time series analysis in the frequency domain,10.1109/78.738253,IEEE Transactions on Signal Processing,Rik Pintelon,Johan Schoukens

Time series analysis in the frequency domain   (Citations: 13)
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This correspondence presents a parametric frequency domain identification algorithm for autoregressive moving average (ARMA) processes that does not suffer from spectral leakage errors. It is based on an extended transfer function model that takes into account the begin and end effect of the finite data record. The relationship with the one-step-ahead prediction error method is established. The advantages of the proposed method are easy prefiltering and leakage-free spectral representation of the raw data
Journal: IEEE Transactions on Signal Processing - TSP , vol. 47, no. 1, pp. 206-210, 1999
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    • ...In fact, AR estimation can be approached from a frequency perspective as well [11]...
    • ...This spectral leakage may cause a biased solution [11]...
    • ...From our experience with many other simulated scenarios that we explored, the answer thereto lies on the spectral leakage caused by the discrete Fourier transform [11], and disregarded in the problem statement...
    • ...One way to compensate the spectral leakage is with the methodology proposed in [11]...

    Luis Weruaga. Frequency-Selective Noise-Compensated Autoregressive Estimation

    • ...For the sake of simplicity, this leakage, which has been object of careful analysis [14], will be disregarded in the forthcoming analysis...
    • ...As stated in [13], [14], the AR estimation from the spectral samples corresponds to the minimization of the following functional:...

    Luis Weruaga. All-Pole Estimation in Spectral Domain

    • ...The difference between (2) and (3) is negligible for large . In [9] this frequency domain approach is further refined by also taking the initial state of the noise filter into account to obtain a leakage free spectral representation...

    Anders Blomqvistet al. On The Relation Between Weighted Frequency-Domain Maximum-Likelihood P...

    • ...End effects from LTV operations, which are more complicated than end effects from LTI operations, cannot be removed using extended transfer function approaches [11]...
    • ...As a brief comparison, the extended transfer function method of [11] attempts to subtract out the effects of spectral leakage, while the parallel-structure method attempts to eliminate systematic errors using common-mode rejection...
    • ...As a result, the method of [11] is simpler to implement...
    • ...For example, the method of [11] is not applicable to removing artifacts from an LTV detrend...

    DAVID S. BAYARDet al. Performance Characterization of a Stellar Interferometer

    • ...This can be done either in the time domain [1] or in the frequency domain [2] leading to exactly the same results [14]...

    Fjo De Ridderet al. Modified AIC and MDL model selection criteria for short data records

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