Linear Estimation of Stationary Autoregressive Processes
Joint Authors
Source
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-02-14
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Electronic engineering
Information Technology and Computer Science
Abstract EN
Consider a sequence of an mth-order Autoregressive (AR) stationary discrete-time process and assume that at least m−1 consecutive neighboring samples of an unknown sample are available.
It is not important that the neighbors are from one side or are from both the left and right sides.
In this paper, we find explicit solutions for the optimal linear estimation of the unknown sample in terms of the neighbors.
We write the estimation errors as the linear combination of innovation noises.
We also calculate the corresponding mean square errors (MSE).
To the best of our knowledge, there is no explicit solution for this problem.
The known solutions are the implicit ones through orthogonality equations.
Also, there are no explicit solutions when fewer than m−1 samples are available.
The order of the process (m) and the feedback coefficients are assumed to be known.
American Psychological Association (APA)
Dianat, Reza& Marvasti, Farokh. 2011. Linear Estimation of Stationary Autoregressive Processes. ISRN Signal Processing،Vol. 2011, no. 2011, pp.1-10.
https://search.emarefa.net/detail/BIM-448790
Modern Language Association (MLA)
Dianat, Reza& Marvasti, Farokh. Linear Estimation of Stationary Autoregressive Processes. ISRN Signal Processing No. 2011 (2011), pp.1-10.
https://search.emarefa.net/detail/BIM-448790
American Medical Association (AMA)
Dianat, Reza& Marvasti, Farokh. Linear Estimation of Stationary Autoregressive Processes. ISRN Signal Processing. 2011. Vol. 2011, no. 2011, pp.1-10.
https://search.emarefa.net/detail/BIM-448790
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-448790