A widely linear complex autoregressive process of order one
File(s)
Accepted version
Author(s)
Sykulski, Adam M
Olhede, Sofia C
Lilly, Jonathan M
Type
Journal Article
Abstract
We propose a simple stochastic process for modeling improper or noncircular complex-valued signals. The process is a natural extension of a complex-valued autoregressive process, extended to include a widely linear autoregressive term. This process can then capture elliptical, as opposed to circular, stochastic oscillations in a bivariate signal. The process is order one and is more parsimonious than alternative stochastic modeling approaches in the literature. We provide conditions for stationarity, and derive the form of the covariance and relation sequence of this model. We describe how parameter estimation can be efficiently performed both in the time and frequency domain. We demonstrate the practical utility of the process in capturing elliptical oscillations that are naturally present in seismic signals.
Date Issued
2016-12-01
Date Acceptance
2016-07-17
Citation
IEEE Transactions on Signal Processing, 2016, 64 (23), pp.6200-6210
ISSN
1053-587X
Publisher
IEEE
Start Page
6200
End Page
6210
Journal / Book Title
IEEE Transactions on Signal Processing
Volume
64
Issue
23
Copyright Statement
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000386232300010&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
autoregressive processes
BANDWIDTH
Engineering
Engineering, Electrical & Electronic
maximum likelihood estimation
MULTIPLE
parameter estimation
PHASE
Science & Technology
seismic measurements
SIGNALS
spectral analysis
Technology
Time series analysis
TIME-SERIES
Publication Status
Published
Date Publish Online
2016-08-10