Title :
On the existence of autoregressive models for third-order cumulant matching
Author :
Raghuveer, M.R. ; Dianat, Soheil A.
Author_Institution :
Dept. of Electr. Eng., Rochester Inst. of Technol., NY, USA
fDate :
12/1/1989 12:00:00 AM
Abstract :
Necessary and sufficient conditions are provided for the third-moment sequence of a white-noise-driven finite-order AR (autoregressive) model to match given samples of the third-moment sequence of an arbitrary stationary process. The conditions lead to a set of nonlinear equations that are solved for the model parameters. A method for finding the third-moment sequence of a white-noise-driven AR model from its parameters is also provided. One of the key results is that, unlike a finite set of autocorrelation samples, a finite set of third-moment sequence samples is not always linearly extendable to an infinite third-moment sequence
Keywords :
filtering and prediction theory; spectral analysis; arbitrary stationary process; autoregressive models; filtering; model parameters; nonlinear equations; spectral analysis; third-moment sequence; third-order cumulant matching; white-noise-driven finite-order; Additive noise; Autocorrelation; Data mining; Filters; Gaussian noise; Nonlinear equations; Random processes; Spectral analysis; Sufficient conditions; White noise;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
