Global exponential estimates of stochastic Cohen-Grossberg neural networks with time delay
Global exponential estimates of stochastic Cohen-Grossberg neural networks with time delay
This paper is concerned with the exponential estimating problem for Cohen-Grossberg neural networks with time delay and stochastic disturbance. A sufficient condition, which does not only guarantee the global exponential stability but also provides more exact characterization on the decay rate and the coefficient, is established in terms of the Lyapunov-Krasovskii functional approach and the linear matrix inequality (LMI) technique. The estimates of the decay rate and the coefficient are obtained by solving a set of LMIs, which can be checked easily by effective algorithms. In addition, slack matrices are introduced to reduce the conservatism of the condition. A numerical example is provided to illustrate the effectiveness of the theoretical results.
978-1-4244-0817-7
459-464
Shu, Zhan
ea5dc18c-d375-4db0-bbcc-dd0229f3a1cb
Lam, James
3eea3836-efda-430c-9ad4-ae4f3d4b8c4a
May 2007
Shu, Zhan
ea5dc18c-d375-4db0-bbcc-dd0229f3a1cb
Lam, James
3eea3836-efda-430c-9ad4-ae4f3d4b8c4a
Shu, Zhan and Lam, James
(2007)
Global exponential estimates of stochastic Cohen-Grossberg neural networks with time delay.
2007 ICCA IEEE International Conference on Control and Automation, Guangzhou, China.
30 May - 01 Jun 2007.
.
(doi:10.1109/ICCA.2007.4376399).
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper is concerned with the exponential estimating problem for Cohen-Grossberg neural networks with time delay and stochastic disturbance. A sufficient condition, which does not only guarantee the global exponential stability but also provides more exact characterization on the decay rate and the coefficient, is established in terms of the Lyapunov-Krasovskii functional approach and the linear matrix inequality (LMI) technique. The estimates of the decay rate and the coefficient are obtained by solving a set of LMIs, which can be checked easily by effective algorithms. In addition, slack matrices are introduced to reduce the conservatism of the condition. A numerical example is provided to illustrate the effectiveness of the theoretical results.
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Published date: May 2007
Venue - Dates:
2007 ICCA IEEE International Conference on Control and Automation, Guangzhou, China, 2007-05-30 - 2007-06-01
Organisations:
Mechatronics
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Local EPrints ID: 199997
URI: http://eprints.soton.ac.uk/id/eprint/199997
ISBN: 978-1-4244-0817-7
PURE UUID: 01628c0a-1ce3-4188-9e21-42e98e891aa4
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Date deposited: 01 Nov 2011 10:20
Last modified: 14 Mar 2024 04:18
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Author:
Zhan Shu
Author:
James Lam
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