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

Alimorad Mahmoudi

International Journal of Stochastic Analysis, 2014, vol. 2014, 1-5

Abstract:

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.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/IJSA/2014/247274.pdf (application/pdf)
http://downloads.hindawi.com/journals/IJSA/2014/247274.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnijsa:247274

DOI: 10.1155/2014/247274

Access Statistics for this article

More articles in International Journal of Stochastic Analysis from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().