Table of Contents
International Journal of Stochastic Analysis
Volume 2014, Article ID 247274, 5 pages
Research Article

Adaptive Algorithm for Estimation of Two-Dimensional Autoregressive Fields from Noisy Observations

Electrical Engineering Department, Shahid Chamran University, Ahvaz, Iran

Received 26 September 2014; Revised 4 December 2014; Accepted 11 December 2014; Published 25 December 2014

Academic Editor: Nikolai N. Leonenko

Copyright © 2014 Alimorad Mahmoudi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper deals with the problem of two-dimensional autoregressive (AR) estimation from noisy observations. The Yule-Walker equations are solved using adaptive steepest descent (SD) algorithm. Performance comparisons are made with other existing methods to demonstrate merits of the proposed method.