DocumentCode :
1745022
Title :
A new learning algorithm for pattern classification using cellular neural networks
Author :
Grassi, Giuseppe ; Sciascio, Eugeizio Di
Author_Institution :
Dipt. di Ingegneria dell´´Innovazione, Lecce Univ., Italy
Volume :
3
fYear :
2001
fDate :
6-9 May 2001
Firstpage :
652
Abstract :
In this paper a new learning algorithm for pattern classification using cellular neural networks is described. In particular, it is shown that patterns belonging to the training set as well as patterns outside it can be reliably classified using the proposed algorithm. Finally, comparisons with well-established classification techniques are carried out, with the aim to highlight the performances of the approach developed herein
Keywords :
cellular neural nets; learning (artificial intelligence); pattern classification; cellular neural networks; classification techniques; learning algorithm; pattern classification; training set; Artificial intelligence; Cellular neural networks; Classification algorithms; Convergence; Digital images; Feedback; Image coding; Information retrieval; Intelligent networks; Pattern classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International Symposium on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-6685-9
Type :
conf
DOI :
10.1109/ISCAS.2001.921395
Filename :
921395
Link To Document :
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