DocumentCode :
2037717
Title :
Locally-interconnected cellular architectures for multisensor data fusion
Author :
Baglio, Salvatore ; Graziani, Salvatore ; Manganaro, Gabriele ; Pitrone, Nicola
Author_Institution :
Dipartimento Elettrico, Elettron. e Sistemistico, Catania Univ., Italy
Volume :
2
fYear :
1996
fDate :
1996
Firstpage :
843
Abstract :
An overview of cellular neural networks (CNNs) and their applications is presented in this paper. CNNs are nonlinear dynamic systems made up of a large number of locally connected units named “cells”. They have been often applied to modeling and simulation of large scale systems in physics, biology and a lot of other different areas because of their powerful real-time processing capabilities. The CNNs basics and their main applications reported in literature are dealt with. In particular the suitability of this new paradigm for possible application in the field of multisensor fusion and integration is investigated
Keywords :
cellular arrays; computerised instrumentation; image processing; learning (artificial intelligence); neural net architecture; nonlinear dynamical systems; sensor fusion; stability; biology; cellular neural networks; integration; large scale systems; locally connected units; locally-interconnected cellular architectures; modeling; multisensor data fusion; multisensor fusion; nonlinear dynamic systems; physics; real-time processing; simulation; Biological system modeling; Cellular neural networks; Circuits; Cloning; Electronic mail; Large-scale systems; Nonlinear equations; Power system modeling; Prototypes; Signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1996. IMTC-96. Conference Proceedings. Quality Measurements: The Indispensable Bridge between Theory and Reality., IEEE
Conference_Location :
Brussels
Print_ISBN :
0-7803-3312-8
Type :
conf
DOI :
10.1109/IMTC.1996.507287
Filename :
507287
Link To Document :
بازگشت