Title :
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
fDate :
9/1/2000 12:00:00 AM
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;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
