DocumentCode
396195
Title
On the prediction of period-doubling bifurcations in almost reciprocal cellular neural networks
Author
Di Marco, M. ; Forti, M. ; Tesi, A.
Author_Institution
Dipt. di Ingegneria dell´´Informazione, Siena Univ., Italy
Volume
3
fYear
2003
fDate
25-28 May 2003
Abstract
The Harmonic Balance (HB) method is exploited for addressing the possible existence of period-doubling bifurcations, and complex dynamics, in a class of almost symmetric Cellular Neural Networks (CNNs). In particular, sets of CNNs parameters close to symmetry, for which period-doubling bifurcations are predicted by the HB method, are singled out. The reliability and accuracy of these predictions are shown by means of computer simulations.
Keywords
bifurcation; cellular neural nets; neural chips; CNNs; Harmonic Balance method; almost reciprocal cellular neural networks; complex dynamics; computer simulations; period-doubling bifurcations; reliability; Bifurcation; Cellular neural networks; Computer network reliability; Integrated circuit interconnections; Intelligent networks; Limit-cycles; Neural networks; Neurons; Robust stability; Symmetric matrices;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2003. ISCAS '03. Proceedings of the 2003 International Symposium on
Print_ISBN
0-7803-7761-3
Type
conf
DOI
10.1109/ISCAS.2003.1205084
Filename
1205084
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