In this paper a Cellular Fuzzy Associative Memory containing fuzzy rules for gray image fuzzification is designed, considered as a subsystem of a CNN-based architecture able to store bidimensional patterns. After establishing the fuzzy rules which characterize the required FAM, these rules are properly codified and stored in a Cellular Nonlinear Network behaving as a memory. A numerical example concerning with the stereoscopic vision of a mobile robot is reported to show how the synthesized memory can process bidimensional patterns for robotic vision purposes.
Synthesis of a Cellular Nonlinear Network for a Fuzzy Associative Memory in Stereoscopic Vision / Carnimeo, L.; Giaquinto, A. - In: Advances in systems engineering, signal processing and communications / [a cura di] Nikos E. Mastorakis. - STAMPA. - Athens, Greece : World Scientific Engineering Society Press, 2002. - ISBN 960-8052-696. - pp. 128-131
Synthesis of a Cellular Nonlinear Network for a Fuzzy Associative Memory in Stereoscopic Vision
Carnimeo, L.;Giaquinto, A.
2002-01-01
Abstract
In this paper a Cellular Fuzzy Associative Memory containing fuzzy rules for gray image fuzzification is designed, considered as a subsystem of a CNN-based architecture able to store bidimensional patterns. After establishing the fuzzy rules which characterize the required FAM, these rules are properly codified and stored in a Cellular Nonlinear Network behaving as a memory. A numerical example concerning with the stereoscopic vision of a mobile robot is reported to show how the synthesized memory can process bidimensional patterns for robotic vision purposes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
