Title :
Synchronization of hyperchaotic cellular neural networks: a system theory approach
Author :
Grassi, Giuseppe ; Mascolo, Saverio
Author_Institution :
Dipt. di Math., Lecce Univ., Italy
Abstract :
In recent years synchronization of chaotic dynamics has received ever increasing attention. Herein, cellular neural networks (CNNs) are considered as a tool for generating hyperchaotic behaviors. By exploiting a system theory approach, a technique for synchronizing a large class of CNNs is developed. In particular, a necessary and sufficient condition for hyperchaos synchronization is given, which is based on the controllability property of linear systems. Finally, in order to show the effectiveness of the proposed technique, the synchronization of a CNN constituted by Chua´s circuits is illustrated
Keywords :
cellular neural nets; chaos; controllability; synchronisation; system theory; CNN; Chua circuits; controllability; hyperchaotic cellular neural networks; linear systems; necessary and sufficient condition; synchronization; system theory; Cellular neural networks; Chaotic communication; Controllability; Integrated circuit interconnections; Linear systems; Neurodynamics; Neurons; Pattern formation; State-space methods; Very large scale integration;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.685999