Global stability of cellular neural networks with constant and variable delays
Nonlinear Analysis: Theory, Methods & Applications
Global Asymptotic Stability Analysis of Neural Networks with Time-Varying Delays
Neural Processing Letters
Global Stability of Neural Networks with Time-Varying Delays
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Stabilisation of Cellular Neural Networks with time-varying delays and reaction-diffusion terms
International Journal of Intelligent Systems Technologies and Applications
On asymptotic stability of discrete-time non-autonomous delayed Hopfield neural networks
Computers & Mathematics with Applications
A New LMI-Based Stability Criteria for Delayed Cellular Neural Networks
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Almost sure exponential stability of recurrent neural networks with Markovian switching
IEEE Transactions on Neural Networks
Stability in cellular neural networks with a piecewise constant argument
Journal of Computational and Applied Mathematics
A new global asymptotic stability result for delayed cellular neural networks
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Novel weighting-delay-based stability criteria for recurrent neural networks with time-varying delay
IEEE Transactions on Neural Networks
Exponential stability of delayed Cellular Neural Networks with large impulses
International Journal of Systems, Control and Communications
Leakage Delays in T---S Fuzzy Cellular Neural Networks
Neural Processing Letters
Stability of non-autonomous delayed cellular neural networks
CIS'04 Proceedings of the First international conference on Computational and Information Science
New stability results for delayed neural networks
KI'05 Proceedings of the 28th annual German conference on Advances in Artificial Intelligence
Neural networks for optimization problem with nonlinear constraints
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Global exponential stability of recurrent neural networks with time-varying delay
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Global exponential stability of cellular neural networks with time-varying delays and impulses
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Globally exponential stability of non-autonomous delayed neural networks
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Improved global exponential stability criteria of cellular neural networks with time-varying delays
Mathematical and Computer Modelling: An International Journal
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Hi-index | 0.00 |
In this paper, a new sufficient condition is given for the uniqueness and global asymptotic stability of the equilibrium point for delayed cellular neural networks (DCNNs). This condition imposes constraints on the feedback and delayed feedback matrices of a DCNN independently of the delay parameter. This result is also compared with the previous results derived in the literature.