Nonlinear Dynamics and Chaos in Fractional-Order Hopfield Neural Networks with Delay
A fractional-order two-neuron Hopfield neural network with delay is proposed based on the classic well-known Hopfield neural networks, and further, the complex dynamical behaviors of such a network are investigated. A great variety of interesting dynamical phenomena, including single-periodic, multi...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Advances in Mathematical Physics |
| Online Access: | http://dx.doi.org/10.1155/2013/657245 |
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| _version_ | 1832560819895795712 |
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| author | Xia Huang Zhen Wang Yuxia Li |
| author_facet | Xia Huang Zhen Wang Yuxia Li |
| author_sort | Xia Huang |
| collection | DOAJ |
| description | A fractional-order two-neuron Hopfield neural network with delay is proposed based on the classic well-known Hopfield neural networks, and further, the complex dynamical behaviors of such a network are investigated. A great variety of interesting dynamical phenomena, including single-periodic, multiple-periodic, and chaotic motions, are found to exist. The existence of chaotic attractors is verified by the bifurcation diagram and phase portraits as well. |
| format | Article |
| id | doaj-art-9702115f8ec84bde9996b3dc268c5c81 |
| institution | Kabale University |
| issn | 1687-9120 1687-9139 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Mathematical Physics |
| spelling | doaj-art-9702115f8ec84bde9996b3dc268c5c812025-02-03T01:26:37ZengWileyAdvances in Mathematical Physics1687-91201687-91392013-01-01201310.1155/2013/657245657245Nonlinear Dynamics and Chaos in Fractional-Order Hopfield Neural Networks with DelayXia Huang0Zhen Wang1Yuxia Li2Shandong Key Laboratory of Robotics and Intelligent Technology, College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Information Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaShandong Key Laboratory of Robotics and Intelligent Technology, College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaA fractional-order two-neuron Hopfield neural network with delay is proposed based on the classic well-known Hopfield neural networks, and further, the complex dynamical behaviors of such a network are investigated. A great variety of interesting dynamical phenomena, including single-periodic, multiple-periodic, and chaotic motions, are found to exist. The existence of chaotic attractors is verified by the bifurcation diagram and phase portraits as well.http://dx.doi.org/10.1155/2013/657245 |
| spellingShingle | Xia Huang Zhen Wang Yuxia Li Nonlinear Dynamics and Chaos in Fractional-Order Hopfield Neural Networks with Delay Advances in Mathematical Physics |
| title | Nonlinear Dynamics and Chaos in Fractional-Order Hopfield Neural Networks with Delay |
| title_full | Nonlinear Dynamics and Chaos in Fractional-Order Hopfield Neural Networks with Delay |
| title_fullStr | Nonlinear Dynamics and Chaos in Fractional-Order Hopfield Neural Networks with Delay |
| title_full_unstemmed | Nonlinear Dynamics and Chaos in Fractional-Order Hopfield Neural Networks with Delay |
| title_short | Nonlinear Dynamics and Chaos in Fractional-Order Hopfield Neural Networks with Delay |
| title_sort | nonlinear dynamics and chaos in fractional order hopfield neural networks with delay |
| url | http://dx.doi.org/10.1155/2013/657245 |
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