Evolutionary design of 2-dimensional recursive filters via the computer language GENETICA

Gonos, IF; Virirakis, LI; Mastorakis, NE; Swamy, MNS

dc.contributor.author	Gonos, IF	en
dc.contributor.author	Virirakis, LI	en
dc.contributor.author	Mastorakis, NE	en
dc.contributor.author	Swamy, MNS	en
dc.date.accessioned	2014-03-01T01:24:22Z
dc.date.available	2014-03-01T01:24:22Z
dc.date.issued	2006	en
dc.identifier.issn	1057-7130	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17233
dc.subject	2-D systems	en
dc.subject	Constrained optimization	en
dc.subject	Evolutionary computational system	en
dc.subject	Two-dimensional (2-D) recursive filters	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Evolutionary computational system	en
dc.subject.other	GENETICA	en
dc.subject.other	Recursive digital filters	en
dc.subject.other	Two dimensional (2-D) recursive filters	en
dc.subject.other	Computational methods	en
dc.subject.other	Constrained optimization	en
dc.subject.other	Evolutionary algorithms	en
dc.subject.other	Formal languages	en
dc.subject.other	Logic design	en
dc.subject.other	Recursive functions	en
dc.subject.other	Digital filters	en
dc.title	Evolutionary design of 2-dimensional recursive filters via the computer language GENETICA	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TCSII.2005.862040	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TCSII.2005.862040	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	In this paper, we present a new design method for a class of two-dimensional (2-D) recursive digital filters using an evolutionary computational system. The design of the 2-D filter is reduced to a constrained minimization problem the solution of which is achieved by the convergence of an appropriate evolutionary algorithm. In our approach, the genotypes of potential solutions have a uniform probability within the region of the search space specified by the constraints and zero probability outside this region. This approach is particularly effective as the evolutionary search considers only those potential solutions that respect the constraints. We use the computer language GENETICA, which provides the expressive power necessary to get an accurate problem formulation and supports an adjustable evolutionary computational system. Results of this procedure are illustrated by a numerical example, and compared with those of some previous designs. © 2006 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Circuits and Systems II: Express Briefs	en
dc.identifier.doi	10.1109/TCSII.2005.862040	en
dc.identifier.isi	ISI:000236891400002	en
dc.identifier.volume	53	en
dc.identifier.issue	4	en
dc.identifier.spage	254	en
dc.identifier.epage	258	en