Title :
A new method of nonstationary time series analysis based on inhomogeneous AR equation
Author :
Yokoyama, Yukiko ; Kumazawa, Mineo ; Imanishi, Yuichi ; Mikami, Naoki
Author_Institution :
Dept. of Comput. & Inf. Sci., Univ. of Ind. Technol., Kanagawa, Japan
fDate :
8/1/1997 12:00:00 AM
Abstract :
We propose a new model for nonstationary time series analysis. The model is of a noise-contaminated signal of an AR system excited by a sequence of an input signal represented in terms of orthogonal functions. We also propose an algorithm that enables us to estimate parameters of the AR part and the input signal simultaneously. The models are finally evaluated by testing the recovery of an output signal. Examples of data analysis of the synthetic time series are shown for the ease in which the input signal is represented by a sequence of wavelets
Keywords :
autoregressive processes; data analysis; parameter estimation; sequences; signal processing; time series; wavelet transforms; AR system; data analysis; inhomogeneous AR equation; input signal sequence; noise contaminated signal; nonstationary time series analysis; output signal recovery; parameter estimation; synthetic time series; wavelets sequence; Autoregressive processes; Data analysis; Differential equations; Eigenvalues and eigenfunctions; Information science; Parameter estimation; Stochastic processes; Testing; Time series analysis; Wavelet analysis;
Journal_Title :
Signal Processing, IEEE Transactions on
