A Comparative Study of Pattern Recognition Algorithms for Classification of Ultrasonic Signals

Anastassopoulos, A; Nikolaidis, V; Philippidis, T

dc.contributor.author	Anastassopoulos, A	en
dc.contributor.author	Nikolaidis, V	en
dc.contributor.author	Philippidis, T	en
dc.date.accessioned	2014-03-01T01:47:46Z
dc.date.available	2014-03-01T01:47:46Z
dc.date.issued	1999	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25313
dc.subject	Classification Error	en
dc.subject	Feature Space	en
dc.subject	Neural System	en
dc.subject	Pattern Recognition	en
dc.subject	Problem Complexity	en
dc.subject	Ultrasound	en
dc.subject	Upper Bound	en
dc.subject	Minimum Classification Error	en
dc.subject	Neural Net Work	en
dc.title	A Comparative Study of Pattern Recognition Algorithms for Classification of Ultrasonic Signals	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/s005210050007	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s005210050007	en
heal.publicationDate	1999	en
heal.abstract	An extensive discrimination study was conducted on ultrasonic signals very similar to each other obtained from artificial inserts in a carbon fibre reinforced epoxy plate. The performance of fifteen classification schemes consisting of non-parametric pattern recognition and Artificial Neural System (ANS) algorithms is assessed in this paper. The purpose of this study is to define an upper bound for the	en
heal.journalName	Neural Computing and Applications	en
dc.identifier.doi	10.1007/s005210050007	en