Title :
Structural stability of least squares prediction methods
Author :
Idier, Jérôme ; Giovannelli, Jean-François
Author_Institution :
Lab. des Signaux et Syst., Supelec, Gif-sur-Yvette, France
fDate :
11/1/1998 12:00:00 AM
Abstract :
A structural stability condition is sought for least squares linear prediction methods in the given data case. Save the Toeplitz case, the structure of the normal equation matrix yields no acknowledged guarantee of stability. Here, a new sufficient condition is provided, and several least squares prediction methods are shown to be structurally stable
Keywords :
filtering theory; least squares approximations; matrix algebra; prediction theory; stability; Toeplitz matrix; displacement matrix; least squares linear prediction methods; linear prediction filters; normal equation matrix; positive semidefinite matrix; structural stability condition; sufficient condition; Autocorrelation; Equations; Filters; Least squares methods; Prediction methods; Robustness; Stability; Statistical distributions; Structural engineering; Sufficient conditions;
Journal_Title :
Signal Processing, IEEE Transactions on
