Title :
On contraction analysis of synchronization of neuron networks
Author :
Solís-Perales, G. ; Obregón-Pulido, G.
Author_Institution :
Dept. de Electron., Univ. de Guadalajara, Guadalajara, Mexico
Abstract :
The synchronization of neuron networks using the contraction theory is reported in this contribution. The contraction theory provides a simple method to determine convergence of trajectories of the systems in the network instead of the Master Stability Function and the calculation of Lyapunov exponents. The objective is to determine the contraction region where once the trajectories reach such region they will converge each other and remain in such a contraction region. Such a condition lies mainly on the system parameters, network topology and coupling strength.
Keywords :
Lyapunov methods; network topology; neural nets; stability; Lyapunov exponents; contraction analysis; contraction theory; coupling strength; master stability function; network topology; neuron network synchronization; system parameters; trajectory convergence; Complex networks; Convergence; Couplings; Neurons; Stability analysis; Synchronization; Trajectory;
Conference_Titel :
Robotics Symposium, 2011 IEEE IX Latin American and IEEE Colombian Conference on Automatic Control and Industry Applications (LARC)
Conference_Location :
Bogota
Print_ISBN :
978-1-4577-1689-8
DOI :
10.1109/LARC.2011.6086840
