Chaotic neural network with self-feedback of trigonometric function and its application

Author

Xu, Yaoqun ; He, Shaoping

Author_Institution

Inst. of Syst. Eng., Harbin Univ. of Commerce, Harbin, China

fYear

2009

fDate

17-19 June 2009

Firstpage

3244

Lastpage

3248

Abstract

A chaotic neural network with self-feedback of trigonometric function is presented by introducing non-linear trigonometric function as self-feedback of chaotic neural network. The reversed bifurcation and the maximum Lyapunov exponent of the chaotic neuron are given. This chaotic neural network is used to the 10-city traveling salesman problem (TSP), and the influence of trigonometric function self-feedback on TSP is analyzed. The simulation on TSP indicates that the chaotic neural network with self-feedback of trigonometric function can realize the global optimization with faster speed and that the optimization performance of the proposed chaotic neural network is superior to that of the network with linear self-feedback.

Keywords

Lyapunov methods; bifurcation; chaos; neural nets; travelling salesman problems; 10-city traveling salesman problem; chaotic neural network; chaotic neuron; global optimization; maximum Lyapunov exponent; nonlinear trigonometric function; reversed bifurcation; selffeedback; Bifurcation; Business; Chaos; Electronic mail; Helium; Hopfield neural networks; Neural networks; Neurons; Systems engineering and theory; Traveling salesman problems; TSP; chaotic neural network; non-linear self-feedback; trigonometric function;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference, 2009. CCDC '09. Chinese

Conference_Location

Guilin

Print_ISBN

978-1-4244-2722-2

Electronic_ISBN

978-1-4244-2723-9

Type

conf

DOI

10.1109/CCDC.2009.5192138

Filename

5192138