Analog cellular networks for multisensor fusion and control

Author

Arena, P. ; Baglio, S. ; Fortuna, L. ; Graziani, S.

Author_Institution

Dipt. di Elettrico, Elettronico e Sistemistico, Catania Univ., Italy

Volume

47

Issue

9

fYear

2000

fDate

9/1/2000 12:00:00 AM

Firstpage

1378

Lastpage

1382

Abstract

Analog modular architectures, derived from the computational paradigm of state-controlled cellular neural networks (SC-CNNs), are considered in this brief to process signals gathered from a distributed set of sensors. A novel design methodology for choosing the "local" system parameters so as to obtain the desired "global" signal processing function is proposed together with some theoretical results on sufficient conditions that guarantee asymptotic stability. An experimental prototype of cellular neural network for multisensor data fusion and control applications is presented and its adoption in the field of smart structures is discussed.

Keywords

analogue processing circuits; asymptotic stability; cellular neural nets; distributed sensors; intelligent structures; sensor fusion; analog cellular networks; asymptotic stability; design methodology; distributed sensors; global signal processing function; local system parameters; multisensor fusion; smart structures; state-controlled cellular neural networks; Analog computers; Asymptotic stability; Cellular neural networks; Computer architecture; Computer networks; Design methodology; Distributed computing; Land mobile radio cellular systems; Signal processing; Sufficient conditions;

fLanguage

English

Journal_Title

Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on

Publisher

ieee

ISSN

1057-7122

Type

jour

DOI

10.1109/81.883333

Filename

883333