Wyszukiwarka
Damian Chojnacki
Zatrudnienie
Słowa kluczowe Pomoc
- autoregressive spectrum estimation
- dwukierunkowy algorytm drabinkowy
- estymacja widmowej gestosci mocy niestacjonarnych procesow stochastycznych
- final prediction error
- identification of nonstationary processes, selection of model order, selection of estimation memory
- identification of nonstationary systems
- lattice algorithms
- lattice filter
- metoda usredniania modeli
- parametric spectrum estimation
Publikacje
Filtry
wszystkich: 6
Katalog Publikacji
Rok 2019
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes
PublikacjaAutoregressive modeling is a widespread parametricspectrum estimation method. It is well known that, in the caseof stationary processes with unknown order, its accuracy canbe improved by averaging models of different complexity usingsuitably chosen weights. The paper proposes an extension of thistechnique to the case of multivariate locally stationary processes.The proposed solution is based on local autoregressive...
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Parametryczna estymacja widma lokalnie stacjonarnych procesów losowych
PublikacjaW niniejszej pracy doktorskiej opisano nowe metody estymacji widmowej gestosci mocy niestacjonarnych procesów stochastycznych. Przedstawione w rozprawie rozwiazania, takie jak dwukierunkowy algorytm drabinkowy z zapominaniem wykładniczym oraz metoda usredniania modeli umozliwiaja precyzyjna estymacje charakterystyk widmowych. Przeprowadzone symulacje potwierdziły, ze opracowane algorytmy daja zadowalajace rezultaty zarówno w przypadku...
Rok 2018
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Identification of nonstationary processes using noncausal bidirectional lattice filtering
PublikacjaThe problem of off-line identification of a nonstationary autoregressive process with a time-varying order and a time-varying degree of nonstationarity is considered and solved using the parallel estimation approach. The proposed parallel estimation scheme is made up of several bidirectional (noncausal) exponentially weighted lattice algorithms with different estimation memory and order settings. It is shown that optimization of...
Rok 2017
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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On autoregressive spectrum estimation using the model averaging technique
PublikacjaThe problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select...
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