TY - JOUR
T1 - On the synchronization of neural networks containing time-varying delays and sector nonlinearity
AU - Yan, Jun Juh
AU - Lin, Jui Sheng
AU - Hung, Meei Ling
AU - Liao, Teh Lu
PY - 2007/1/22
Y1 - 2007/1/22
N2 - We present a systematic design procedure for synchronization of neural networks subject to time-varying delays and sector nonlinearity in the control input. Based on the drive-response concept and the Lyapunov stability theorem, a memoryless decentralized control law is proposed which guarantees exponential synchronization even when input nonlinearity is present. The supplementary requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed control scheme. A four-dimensional Hopfield neural network with time-varying delays is presented as the illustrative example to demonstrate the effectiveness of the proposed synchronization scheme.
AB - We present a systematic design procedure for synchronization of neural networks subject to time-varying delays and sector nonlinearity in the control input. Based on the drive-response concept and the Lyapunov stability theorem, a memoryless decentralized control law is proposed which guarantees exponential synchronization even when input nonlinearity is present. The supplementary requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed control scheme. A four-dimensional Hopfield neural network with time-varying delays is presented as the illustrative example to demonstrate the effectiveness of the proposed synchronization scheme.
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U2 - 10.1016/j.physleta.2006.08.083
DO - 10.1016/j.physleta.2006.08.083
M3 - Article
AN - SCOPUS:33751430979
SN - 0375-9601
VL - 361
SP - 70
EP - 77
JO - Physics Letters, Section A: General, Atomic and Solid State Physics
JF - Physics Letters, Section A: General, Atomic and Solid State Physics
IS - 1-2
ER -