A family of computationally efficient algorithms for multichannel signal processing-A tutorial review

Kalouptsidis, N; Manolakis, D; Carayannis, G

dc.contributor.author	Kalouptsidis, N	en
dc.contributor.author	Manolakis, D	en
dc.contributor.author	Carayannis, G	en
dc.date.accessioned	2014-03-01T01:38:30Z
dc.date.available	2014-03-01T01:38:30Z
dc.date.issued	1983	en
dc.identifier.issn	01651684	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/22211
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0020496780&partnerID=40&md5=4f936542a346de75b066bef11b8e6bcc	en
dc.subject	fast algorithms	en
dc.subject	Multichannel signal processing (MSP)	en
dc.subject	parametric signal modelling	en
dc.subject	Toeplitz and banded Toeplitz matrices	en
dc.subject	Wiener filtering	en
dc.subject.other	MULTICHANNEL SIGNAL PROCESSING	en
dc.subject.other	SIGNAL PROCESSING	en
dc.title	A family of computationally efficient algorithms for multichannel signal processing-A tutorial review	en
heal.type	journalArticle	en
heal.publicationDate	1983	en
heal.abstract	This paper is concerned with the solution of block linear systems arising in multichannel digital signal processing. First the general problem of block matrix inversion and linear system solution is considered and a corresponding algorithm, recursive in nature, is developed, together with a block form of triangularization theorem. Subsequently these general schemes are specialized to block Toeplitz structures yielding most existing efficient algorithms. To this respect, matrices related to multichannel Wiener filtering, AR and ARMA modelling as well as s+1 steps ahead prediction are examined and related algorithms are described. Finally block banded Toeplitz systems are considered and two new efficient algorithms are presented, one recursive in nature and the other FFT based. They constitute natural extensions of methods already available for the single channel case and their derivation is simple due to the unified approach introduced in this paper. © 1983.	en
heal.journalName	Signal Processing	en
dc.identifier.volume	5	en
dc.identifier.issue	1	en
dc.identifier.spage	5	en
dc.identifier.epage	19	en