state estimation for neural networks with leakage delay and time-varying delays
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ID: 176069
2013
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Abstract
The state estimation problem is investigated for neural networks with leakage delay and time-varying
delay as well as for general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and
employing matrix inequality techniques, a delay-dependent linear matrix inequalities (LMIs) condition is developed
to estimate the neuron state with some observed output measurements such that the error-state system is globally
asymptotically stable. An example is given to show the effectiveness of the proposed criterion.
| Reference Key |
liang2013abstractstate
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|---|---|
| Authors | ;Jing Liang;Zengshun Chen;Qiankun Song |
| Journal | science and technology of advanced materials |
| Year | 2013 |
| DOI |
10.1155/2013/289526
|
| URL | |
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