Set-valued derivative and Lyapunov method for full-range cellular neural networks

Author(s):  
M. Di Marco ◽  
M. Forti ◽  
M. Grazzini ◽  
L. Pancioni
Author(s):  
Ivanka M. Stamova ◽  
Stanislav Simeonov

This research introduces a model of a delayed reaction–diffusion fractional neural network with time-varying delays. The Mittag–Leffler-type stability of the solutions is investigated, and new sufficient conditions are established by the use of the fractional Lyapunov method. Mittag–Leffler-type synchronization criteria are also derived. Three illustrative examples are established to exhibit the proposed sufficient conditions.


2003 ◽  
Vol 13 (05) ◽  
pp. 367-375 ◽  
Author(s):  
JINDE CAO ◽  
JUN WANG ◽  
XIAOFENG LIAO

In this paper, a new sufficient condition is given for the global asymptotic stability and global exponential output stability of a unique equilibrium points of delayed cellular neural networks (DCNNs) by using Lyapunov method. This condition imposes constraints on the feedback matrices and delayed feedback matrices of DCNNs and is independent of the delay. The obtained results extend and improve upon those in the earlier literature, and this condition is also less restrictive than those given in the earlier references. Two examples compared with the previous results in the literatures are presented and a simulation result is also given.


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