| contributor author | Arik, Sabri | |
| date accessioned | 2020-03-12T18:31:15Z | |
| date available | 2020-03-12T18:31:15Z | |
| date issued | 2014 | |
| identifier issn | 2162-237X | |
| identifier other | 6650046.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/961252?show=full | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | New Criteria for Global Robust Stability of Delayed Neural Networks With Norm-Bounded Uncertainties | |
| type | Journal Paper | |
| contenttype | Metadata Only | |
| identifier padid | 7994018 | |
| subject keywords | Lyapunov methods | |
| subject keywords | asymptotic stability | |
| subject keywords | computational complexity | |
| subject keywords | delays | |
| subject keywords | discrete systems | |
| subject keywords | matrix algebra | |
| subject keywords | neural nets | |
| subject keywords | Lyapunov stability theory | |
| subject keywords | continuous activation functions | |
| subject keywords | delayed neural networks | |
| subject keywords | discrete time delays | |
| subject keywords | equilibrium point | |
| subject keywords | global asymptotic robust stability | |
| subject keywords | homeomorphic mapping theorem | |
| subject keywords | low computational complexity | |
| subject keywords | network parameter uncertainty sets | |
| subject keywords | norm-bounded uncertainties | |
| subject keywords | slope-bounded activation functions | |
| subject keywords | sufficient conditions | |
| subject keywords | symmetric matrices | |
| subject keywords | Asymptotic sta | |
| identifier doi | 10.1109/TNNLS.2013.2287279 | |
| journal title | Neural Networks and Learning Systems, IEEE Transactions on | |
| journal volume | 25 | |
| journal issue | 6 | |
| filesize | 241806 | |
| citations | 0 | |
