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
A new learning algorithm for pattern classification using cellular neural networks / Grassi, G.; Di Sciascio, E.. - STAMPA. - (2001), pp. 652-655. (Intervento presentato al convegno IEEE International Symposium on Circuits and Systems, ISCAS 2001 tenutosi a Sydney, Australia nel May 6-9, 2001) [10.1109/ISCAS.2001.921395].
A new learning algorithm for pattern classification using cellular neural networks
E. Di Sciascio
2001-01-01
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 hereinI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.