A novel algorithm for unsupervised classification of datasets made up of integer valued patterns by means of Cellular Neural Network (CNN) is proposed. The algorithm is suited both for linearly separable and non linearly, separable data sets. The adopted CNN is n-dimensional and is based on a space-variant template - neighborhood order 1 - to cluster n-dimensional datasets. The choice of a CNN architecture allows a straightforward hardware implementation, particularly suited for bi-dimensional patterns.
Costantini G., C.D. (2006). A pattern classification method based on a spape-variant CNN template. In Proceedings of the 2006 10th IEEE International Workshop on Cellular Neural Networks and Their Applications (pp.216-220). NEW YORK : IEEE.
Autori: | |
Autori: | Costantini G., Casali D., Carota M. |
Titolo: | A pattern classification method based on a spape-variant CNN template |
Nome del convegno: | 10th IEEE International Workshop on Cellular Neural Networks and Their Applications |
Luogo del convegno: | Istanbul, TURKEY |
Anno del convegno: | 28 August 2006 through 30 August 2006 |
Enti collegati al convegno: | Scientific and Technological Research Council of Turkey (TUBITAK);SIEMENS San. ve Tic. A.S.;Office of Naval Research (ONR);IEEE CAS Society |
Rilevanza: | Rilevanza internazionale |
Data di pubblicazione: | 2006 |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/CNNA.2006.341633 |
Settore Scientifico Disciplinare: | Settore ING-IND/31 - Elettrotecnica |
Lingua: | English |
Tipologia: | Intervento a convegno |
Citazione: | Costantini G., C.D. (2006). A pattern classification method based on a spape-variant CNN template. In Proceedings of the 2006 10th IEEE International Workshop on Cellular Neural Networks and Their Applications (pp.216-220). NEW YORK : IEEE. |
Appare nelle tipologie: | 02 - Intervento a convegno |