Extending the CNN paradigm to approximate chaotic systems with multivariable nonlinearities

Author

Arena, Paolo ; Fortuna, Luigi ; Rizzo, Alessandro ; Xibilia, Maria G.

Author_Institution

DEES, Catania Univ., Italy

Volume

5

fYear

2000

fDate

2000

Firstpage

141

Abstract

In this paper it is shown that, with slight modifications, State Controlled CNNs (SC-CNNs) are able to approximate the behaviour of a class of complex dynamics with multivariable nonlinearities. In particular, in the so-called Extended SC-CNN defined in this work, the output nonlinearity shape has been modified, and a new template acting on the output function of the cell has been introduced. The needed circuitry to extend SC-CNNs, together with SPICE simulations of the new system, are here reported in order to confirm the suitability of the approach

Keywords

SPICE; cellular neural nets; chaos; nonlinear dynamical systems; nonlinear network analysis; SC-CNN; SPICE; chaotic system; circuit simulation; complex dynamics; multivariable nonlinearity; state controlled cellular neural network; template; Cellular neural networks; Chaos; Chaotic communication; Circuit simulation; Control nonlinearities; Integrated circuit interconnections; Nonlinear circuits; Nonlinear dynamical systems; SPICE; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on

Conference_Location

Geneva

Print_ISBN

0-7803-5482-6

Type

conf

DOI

10.1109/ISCAS.2000.857383

Filename

857383