Exact simulation of noncircular or improper complex-valued stationary Gaussian processes using circulant embedding
File(s)1605.05278v2.pdf (252.54 KB)
Accepted version
Author(s)
Sykulski, Adam M
Percival, Donald B
Type
Conference Paper
Abstract
This paper provides an algorithm for simulating improper (or noncircular) complex-valued stationary Gaussian processes. The technique utilizes recently developed methods for multi-variate Gaussian processes from the circulant embedding literature. The method can be performed in O(n log 2 n) operations, where n is the length of the desired sequence. The method is exact, except when eigenvalues of prescribed circulant matrices are negative. We evaluate the performance of the algorithm empirically, and provide a practical example where the method is guaranteed to be exact for all n, with an improper fractional Gaussian noise process.
Date Issued
2016-11-10
Date Acceptance
2016-11-01
Citation
2016 IEEE 26TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2016, pp.1-6
ISSN
2161-0363
Publisher
IEEE
Start Page
1
End Page
6
Journal / Book Title
2016 IEEE 26TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP)
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:000392177200032&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Source
26th IEEE International Workshop on Machine Learning for Signal Processing (MLSP)
Subjects
Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
Circulant embedding
improper
noncircular
complex-valued
fractional Gaussian noise
Publication Status
Published
Start Date
2016-09-13
Finish Date
2016-09-16
Coverage Spatial
Salerno, ITALY
Date Publish Online
2016-11-10