Autoregressive models of the random fields : a survey
Joint Authors
Source
Iraqi Journal of Computer, Communications and Control Engineering
Issue
Vol. 20, Issue 2 (30 Apr. 2020), pp.1-9, 9 p.
Publisher
Publication Date
2020-04-30
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Autoregressive (AR) random fields are widely use to describe changes in the status of real-physical objects and implemented for analyzing linear & non-linear models.
AR models are Markov processes with a higher order dependence for one-dimensional time series.
Actually, various estimation methods were used in order to evaluate the autoregression parameters.
Although in many applications background knowledge can often shed light on the search for a suitable model, but other applications lack this knowledge and often require the type of trial errors to choose a model.
This article presents a brief survey of the literatures related to the linear and non-linear autoregression models, including several extensions of the main mode models and the models developed.
The use of autoregression to describe such system requires that they be of sufficiently high orders which leads to increase the computational costs
American Psychological Association (APA)
Abd Al-Kazim, Husayn A.& Ibrahim, Mayyadah S.& Abu al-Raghif, Ali N.. 2020. Autoregressive models of the random fields : a survey. Iraqi Journal of Computer, Communications and Control Engineering،Vol. 20, no. 2, pp.1-9.
https://search.emarefa.net/detail/BIM-972689
Modern Language Association (MLA)
Abd Al-Kazim, Husayn A.…[et al.]. Autoregressive models of the random fields : a survey. Iraqi Journal of Computer, Communications and Control Engineering Vol. 20, no. 2 (Apr. 2020), pp.1-9.
https://search.emarefa.net/detail/BIM-972689
American Medical Association (AMA)
Abd Al-Kazim, Husayn A.& Ibrahim, Mayyadah S.& Abu al-Raghif, Ali N.. Autoregressive models of the random fields : a survey. Iraqi Journal of Computer, Communications and Control Engineering. 2020. Vol. 20, no. 2, pp.1-9.
https://search.emarefa.net/detail/BIM-972689
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 7-9
Record ID
BIM-972689