Mathematical Framework for Pseudo-Spectra of Linear Stochastic Difference Equations

被引:4
作者
Bujosa, Marcos [1 ]
Bujosa, Andres [2 ]
Garcia-Ferrer, Antonio [3 ]
机构
[1] Univ Complutense Madrid, Dept Fundamentos Anal Econ 2, Pozuelo De Alarcon 28223, Spain
[2] Univ Politecn Madrid, ETSI Telecomunicac, Dept Matemat Aplicada Tecnol Informac, E-28040 Madrid, Spain
[3] Univ Autonoma Madrid, Dept Anal Econ Econ Cuantitativa, E-28049 Madrid, Spain
关键词
Spectral analysis; time series; non-stationarity; frequency domain; pseudo-covariance function; linear stochastic difference equations; partial inner product; Extended Fourier Transform; TIME-SERIES MODELS; DYNAMIC HARMONIC REGRESSION; NONSTATIONARY PROCESSES; SIGNAL EXTRACTION; SEASONAL ADJUSTMENT; APPROXIMATIONS; DECOMPOSITION; FLUCTUATIONS; ERROR; NOISE;
D O I
10.1109/TSP.2015.2469640
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Although spectral analysis of stationary stochastic processes has solid mathematical foundations, this is not always so for some non-stationary cases. Here, we establish a rigorous mathematical extension of the classic Fourier spectrum to the case in which there are AR roots in the unit circle, i.e., the transfer function of the linear time-invariant filter has poles on the unit circle. To achieve it we: embed the classical problem in a wider framework, extend the Discrete Time Fourier Transform and defined a new Extended Fourier Transform pair pseudo-covariance function/pseudo-spectrum. Our approach is a proper extension of the classical spectral analysis, within which the Fourier Transform pair auto-covariance function/spectrum is a particular case. Consequently spectrum and pseudo-spectrum coincide when the first one is defined.
引用
收藏
页码:6498 / 6509
页数:12
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