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
Link To Document :
بازگشت