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