The aim of this paper is the proposition of a soft computing approach for solving patter recognition problems. In particular, starting from Shannon’s Fuzzy Entropy, we propose a mathematical model which extracts fuzzy inference with minimal entropy. The proposal approach has been applied to evaluate Synthetic A
A Minimal Fuzzy Entropy Model for Pattern Recognition: Evaluation in a SAR Imagery Application / Barrile, Vincenzo; Cacciola, M; Versaci, M. - (2006), pp. 275-279. (Intervento presentato al convegno 5th WSEAS Int. Conf. on ARTIFICIAL INTELLIGENCE, KNOWLEDGE ENGINEERING and DATA BASES (AIKED '06) tenutosi a Madrid, Spain nel February 15-17, 2006).
A Minimal Fuzzy Entropy Model for Pattern Recognition: Evaluation in a SAR Imagery Application
BARRILE, Vincenzo;VERSACI M
2006-01-01
Abstract
The aim of this paper is the proposition of a soft computing approach for solving patter recognition problems. In particular, starting from Shannon’s Fuzzy Entropy, we propose a mathematical model which extracts fuzzy inference with minimal entropy. The proposal approach has been applied to evaluate Synthetic AI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
