State Estimation for Neural Networks with Leakage Delay and Time-Varying Delays
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...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
|
| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2013/289526 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|---|
| ISSN: | 1085-3375 1687-0409 |