A subspace approach to estimation of autoregressive parameters from noisy measurements

作     者：Davila, CE 

作者机构：So Methodist Univ Dept Elect Engn Dallas TX 75275 USA 

出 版 物：《IEEE TRANSACTIONS ON SIGNAL PROCESSING》 (IEEE Trans Signal Process)

年 卷 期：1998年第46卷第2期

页      面：531-534页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

基　　金：National Science Foundation(BCS-9308028) Whitaker Foundation 

主　　题：Parameter estimation Biomedical measurements Equations Noise measurement Autocorrelation Random processes Linear predictive coding White noise Additive noise Eigenvalues and eigenfunctions 

摘      要：This correspondence describes a method for estimating the parameters of an autoregressive (AR) process from a finite number of noisy measurements, The method uses a modified set of Yule-Walker (YW) equations that lead to a quadratic eigenvalue problem that, when solved, gives estimates of the AR parameters and the measurement noise variance.