Cellular neural networks: a new paradigm for multisensor data fusion

Author

Baglio, S. ; Graziani, S. ; Manganaro, G. ; Pitrone, N.

Author_Institution

Dipartimento Elettrico, Elettronico e Sistemistico, Catania Univ., Italy

Volume

1

fYear

1996

fDate

13-16 May 1996

Firstpage

509

Abstract

In this paper an overview of cellular neural networks (CNNs) and their applications is reported with special attention to some problems in the field of multisensor data fusion. CNNs are nonlinear dynamical systems with a large number of state variables. Moreover, these artificial systems have been often applied to the modelling and simulation of other large scale systems in physics, biology and a lot of other different areas. Applications discussed include image processing, partial differential equation solution and nonlinear phenomena modeling

Keywords

cellular neural nets; image processing; mathematics computing; nonlinear dynamical systems; partial differential equations; sensor fusion; artificial systems; biology; cellular neural networks; image processing; large scale systems; modelling; multisensor data fusion; nonlinear dynamical systems; nonlinear phenomena modeling; partial differential equation solution; physics; simulation; state variables; Artificial neural networks; Biological system modeling; Cellular neural networks; Circuits; Cloning; Delay; Electronic mail; Large-scale systems; Physics; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrotechnical Conference, 1996. MELECON '96., 8th Mediterranean

Conference_Location

Bari

Print_ISBN

0-7803-3109-5

Type

conf

DOI

10.1109/MELCON.1996.551590

Filename

551590