Cumulant-based autocorrelation estimates of non-Gaussian linear processes

Giannakis, GB; Delopoulos, A

dc.contributor.author	Giannakis, GB	en
dc.contributor.author	Delopoulos, A	en
dc.date.accessioned	2014-03-01T01:10:54Z
dc.date.available	2014-03-01T01:10:54Z
dc.date.issued	1995	en
dc.identifier.issn	01651684	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/11482
dc.subject	Asymptotic covariance	en
dc.subject	Consistency	en
dc.subject	Cumulants	en
dc.subject	Non-Gaussian time series: Autocorrelation estimation	en
dc.subject.other	Algorithms	en
dc.subject.other	Correlation methods	en
dc.subject.other	Parameter estimation	en
dc.subject.other	Random processes	en
dc.subject.other	Recursive functions	en
dc.subject.other	Spurious signal noise	en
dc.subject.other	Cumulant-based autocorrelation estimates	en
dc.subject.other	Non Gaussian linear processes	en
dc.subject.other	Signal processing	en
dc.title	Cumulant-based autocorrelation estimates of non-Gaussian linear processes	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/0165-1684(95)00095-X	en
heal.identifier.secondary	http://dx.doi.org/10.1016/0165-1684(95)00095-X	en
heal.publicationDate	1995	en
heal.abstract	Autocorrelation of linear random processes can be expressed in terms of their cumulants. Theoretical insensitivity of the latter to additive Gaussian noise of unknown covariance, is exploited in this paper to develop (within a scale) autocorrelation estimators of linear non-Gaussian time series using cumulants of order higher than two. Windowed projections of third-order cumulants are shown to yield strongly consistent estimators of the autocorrelation sequence. Both batch and recursive algorithms are derived. Asymptotic variance expressions of the proposed estimators are also presented. Simulations are provided to illustrate the performance of the proposed algorithms and compare them with conventional approaches. © 1995.	en
heal.journalName	Signal Processing	en
dc.identifier.doi	10.1016/0165-1684(95)00095-X	en
dc.identifier.volume	47	en
dc.identifier.issue	1	en
dc.identifier.spage	1	en
dc.identifier.epage	17	en