DocumentCode :
2250893
Title :
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
Link To Document :
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