Recent developments in the core of digital signal processing: Non-linear signal processing

Maragos, Petros

dc.contributor.author	Maragos, Petros	en
dc.date.accessioned	2014-03-01T01:48:42Z
dc.date.available	2014-03-01T01:48:42Z
dc.date.issued	1999	en
dc.identifier.issn	10535888	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25574
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0032761711&partnerID=40&md5=c9ebefecd770a632abe36c04624441ec	en
dc.subject.other	Algorithms	en
dc.subject.other	Fractals	en
dc.subject.other	Mathematical models	en
dc.subject.other	Neural networks	en
dc.subject.other	Nonlinear filtering	en
dc.subject.other	Signal detection	en
dc.subject.other	Spurious signal noise	en
dc.subject.other	Homomorphic systems	en
dc.subject.other	Digital signal processing	en
dc.title	Recent developments in the core of digital signal processing: Non-linear signal processing	en
heal.type	journalArticle	en
heal.publicationDate	1999	en
heal.abstract	A small number of groups of classes of nonlinear systems that received attention from the digital signal processing (DSP) community or search is described. They are only samples that indicate the diversity of the nonlinear area. Many classes of nonlinear systems proved to be useful and often necessary, in many problems of filtering, vision, speech, communications, control, and pattern recognition. There will always be a need for nonlinear DSP to provide discrete models and robust numerical algorithms for solving detection/estimation/classification problems related to the applications of nonlinear systems.	en
heal.publisher	IEEE, Piscataway, NJ, United States	en
heal.journalName	IEEE Signal Processing Magazine	en
dc.identifier.volume	16	en
dc.identifier.issue	1	en
dc.identifier.spage	28	en
dc.identifier.epage	31	en