Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial Coupling
A delayed neural network model of two neurons with inertial coupling is dealt with in this paper. The stability is investigated and Hopf bifurcation is demonstrated. Applying the normal form theory and the center manifold argument, we derive the explicit formulas for determining the properties of th...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2012/689319 |
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| _version_ | 1832548496353263616 |
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| author | Changjin Xu Peiluan Li |
| author_facet | Changjin Xu Peiluan Li |
| author_sort | Changjin Xu |
| collection | DOAJ |
| description | A delayed neural network model of two neurons with inertial coupling is dealt with in this paper. The stability is investigated and Hopf bifurcation is demonstrated. Applying the normal form theory and the center manifold argument, we derive the explicit formulas for determining the properties of the bifurcating periodic solutions. An illustrative example is given to demonstrate the effectiveness of the obtained results. |
| format | Article |
| id | doaj-art-dc7980296e3247f28dc2191c361faf34 |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-dc7980296e3247f28dc2191c361faf342025-02-03T06:14:05ZengWileyAbstract and Applied Analysis1085-33751687-04092012-01-01201210.1155/2012/689319689319Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial CouplingChangjin Xu0Peiluan Li1Guizhou Key Laboratory of Economics System Simulation, School of Mathematics and Statistics, Guizhou University of Finance and Economics, Guiyang 550004, ChinaDepartment of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471003, ChinaA delayed neural network model of two neurons with inertial coupling is dealt with in this paper. The stability is investigated and Hopf bifurcation is demonstrated. Applying the normal form theory and the center manifold argument, we derive the explicit formulas for determining the properties of the bifurcating periodic solutions. An illustrative example is given to demonstrate the effectiveness of the obtained results.http://dx.doi.org/10.1155/2012/689319 |
| spellingShingle | Changjin Xu Peiluan Li Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial Coupling Abstract and Applied Analysis |
| title | Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial Coupling |
| title_full | Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial Coupling |
| title_fullStr | Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial Coupling |
| title_full_unstemmed | Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial Coupling |
| title_short | Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial Coupling |
| title_sort | dynamics in a delayed neural network model of two neurons with inertial coupling |
| url | http://dx.doi.org/10.1155/2012/689319 |
| work_keys_str_mv | AT changjinxu dynamicsinadelayedneuralnetworkmodeloftwoneuronswithinertialcoupling AT peiluanli dynamicsinadelayedneuralnetworkmodeloftwoneuronswithinertialcoupling |