AbstractAn autoregressive type approximation is determined from an AR.MA model of physical process by truncating the Taylor expansion of MA part, which is called the T. AR model. The poles of the T.AR model are studied by the aid of the Rouche's theorem of the theory of complex functions. Though the power spectral density of T.AR model converges uniformly to that of AR.MA model, the pole location of T.AR model is quite different from the pole-zero location of AR.MA model. T.AR models have some of original poles of AR.MA model, a “non-robust singular” pole, and poles distributing in a circle in the complex plane which are the statistically equivalent expression of the zero of the AR.MA model closest to the unit circle in the complex plane. T...
Although weights of some system poles of the AR model are asymptotically constant for model order ch...
In this paper we present a pole estimation algorithm which is based on an overdetermined adaptive II...
This paper deals with autoregressive models of singular spectra. The starting point is the assumptio...
AbstractAn autoregressive type approximation is determined from an AR.MA model of physical process b...
AbstractThe non-robust singular pole of a scalar T.AR model which is defined by truncating the Taylo...
AbstractThe non-robust singular pole of a scalar T.AR model which is defined by truncating the Taylo...
AbstractPole locations of a multivariate autoregressive (AR) type model for a Gaussian Markovian pro...
AbstractPole locations of a multivariate autoregressive (AR) type model for a Gaussian Markovian pro...
The autoregressive model is a tool used in time series analysis to describe and model time series da...
In this paper autoregressive (AR) modelling of stationary processes is generalised so that it become...
AbstractThis paper deals with autoregressive (AR) models of singular spectra, whose corresponding tr...
This paper deals with nonstationary autoregressive (AR) models with complex roots on the unit circle...
The autoregressive (AR) model of a random process is interpreted in the light of the Prony's relatio...
My final thesis firstly addresses basic knowledge of the theory of stochastic processes. This is fir...
This dissertation consists of five chapters. In Chapter 1, we collect some fundamental concepts and ...
Although weights of some system poles of the AR model are asymptotically constant for model order ch...
In this paper we present a pole estimation algorithm which is based on an overdetermined adaptive II...
This paper deals with autoregressive models of singular spectra. The starting point is the assumptio...
AbstractAn autoregressive type approximation is determined from an AR.MA model of physical process b...
AbstractThe non-robust singular pole of a scalar T.AR model which is defined by truncating the Taylo...
AbstractThe non-robust singular pole of a scalar T.AR model which is defined by truncating the Taylo...
AbstractPole locations of a multivariate autoregressive (AR) type model for a Gaussian Markovian pro...
AbstractPole locations of a multivariate autoregressive (AR) type model for a Gaussian Markovian pro...
The autoregressive model is a tool used in time series analysis to describe and model time series da...
In this paper autoregressive (AR) modelling of stationary processes is generalised so that it become...
AbstractThis paper deals with autoregressive (AR) models of singular spectra, whose corresponding tr...
This paper deals with nonstationary autoregressive (AR) models with complex roots on the unit circle...
The autoregressive (AR) model of a random process is interpreted in the light of the Prony's relatio...
My final thesis firstly addresses basic knowledge of the theory of stochastic processes. This is fir...
This dissertation consists of five chapters. In Chapter 1, we collect some fundamental concepts and ...
Although weights of some system poles of the AR model are asymptotically constant for model order ch...
In this paper we present a pole estimation algorithm which is based on an overdetermined adaptive II...
This paper deals with autoregressive models of singular spectra. The starting point is the assumptio...