DocumentCode
3547466
Title
Complex dynamics in a class of nearly-symmetric competitive CNNs
Author
Di Marco, M. ; Forti, M. ; Grazzini, M. ; Pancioni, L.
Author_Institution
Dipt. di Ingegneria dell´´Informazione, Siena Univ., Italy
fYear
2005
fDate
23-26 May 2005
Firstpage
4677
Abstract
The paper analyzes bifurcations and complex dynamics in a class of nearly symmetric standard cellular neural networks (CNN). A one-parameter family of fourth-order CNN is introduced, which exhibits a cascade of period-doubling bifurcations leading to the birth of a complex attractor, close to some nominal symmetric CNN. The novelty with respect to previous work on this topic, is that the bifurcations and complex dynamics are obtained for small relative errors with respect to the nominal interconnections. The dynamical properties of the introduced class of fourth-order CNN, which are characterized by negative (inhibitory) interconnections between distinct neurons, are explained on the basis of a technique proposed by Smale (1976) to embed a given dynamical system within a competitive dynamical system of larger order.
Keywords
bifurcation; cellular neural nets; stability; unsupervised learning; cellular neural networks; competitive dynamical system; complex attractor; complex dynamics; distinct neurons; fourth-order CNN; nearly symmetric competitive CNN; negative inhibitory interconnections; one-parameter family; period-doubling bifurcations; Bifurcation; Cellular neural networks; Computer simulation; Displays; Electronic mail; Frequency domain analysis; Neurons; Robust stability; Symmetric matrices; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on
Print_ISBN
0-7803-8834-8
Type
conf
DOI
10.1109/ISCAS.2005.1465676
Filename
1465676
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