Title :
Iterative methods for estimation of 2-D AR parameters using a data-adaptive Toeplitz approximation algorithm
Author :
Eremic, John C. ; Tummala, Murali
Author_Institution :
US Naval Postgraduate Sch., Monterey, CA, USA
Abstract :
A new two-dimensional (2-D) data-adaptive algorithm utilizing the iterative Toeplitz approximation method is presented. This algorithm provides a means for efficient estimation of 2-D AR parameters representing spatially variant data arrays. Its convergence performance is comparable to that of the 2-D recursive least squares (RLS) algorithm but is computationally more efficient. The savings in computation is realized by reducing the size of the matrix to be inverted when solving the AR model normal equations. The ability of the algorithm to estimate accurately the model parameters using very small data sets and various windowing schemes is evaluated. Single quadrant and combined quadrant spectral estimates are compared for quarter-plane and nonsymmetric half-plane regions of support
Keywords :
iterative methods; matrix algebra; parameter estimation; spectral analysis; 2-D AR parameters; 2-D recursive least squares; 2D data adaptive algorithm; AR model normal equations; RLS; convergence performance; data sets; iterative Toeplitz approximation method; matrix size reduction; nonsymmetric half-plane; parameter estimation; quarter-plane; spatially variant data arrays; spectral estimates; windowing; Approximation algorithms; Approximation methods; Autocorrelation; Equations; Iterative algorithms; Iterative methods; Least squares approximation; Parameter estimation; Quadratic programming; Signal processing algorithms;
Conference_Titel :
Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-2470-1
DOI :
10.1109/ACSSC.1991.186445
