Title :
Study on Stability of Equilibrium Point of Asymmetrical Internet Neural Network
Author :
Qi, Dan ; Li, Jian-ping
Author_Institution :
Basic Dept., Logistics Eng. Univ., Chongqing
Abstract :
The stability of equilibrium point of neural network for the large-scale dynamic system is extremely important. This article has studied the stability of equilibrium point of vector differential equation of the asymmetrical internet, proposed to utilize approximate linear equation to study the stability problem of equilibrium point of neural network. This method is simple and effective to examine the equilibrium point of the system whether to be stability. Morever it is very easy to realize the computer simulation.
Keywords :
differential equations; neural nets; Hopfield network; asymmetrical Internet neural network; large-scale dynamic system; neural network equilibrium point; vector differential equation; Artificial neural networks; Computer science; Differential equations; Hopfield neural networks; IP networks; Large-scale systems; Linear approximation; Neural networks; Stability analysis; Symmetric matrices; Equilibrium point; Hopfield network; Stable; eigenvalue;
Conference_Titel :
Apperceiving Computing and Intelligence Analysis, 2008. ICACIA 2008. International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-3427-5
Electronic_ISBN :
978-1-4244-3426-8
DOI :
10.1109/ICACIA.2008.4770043
