Centralized and Decentralized Data-Sampling Principles for Outer-Synchronization of Fractional-Order Neural Networks
This paper aims to investigate the outer-synchronization of fractional-order neural networks. Using centralized and decentralized data-sampling principles and the theory of fractional differential equations, sufficient criteria about outer-synchronization of the controlled fractional-order neural ne...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2017/6290646 |
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| _version_ | 1832548543163793408 |
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| author | Jin-E Zhang |
| author_facet | Jin-E Zhang |
| author_sort | Jin-E Zhang |
| collection | DOAJ |
| description | This paper aims to investigate the outer-synchronization of fractional-order neural networks. Using centralized and decentralized data-sampling principles and the theory of fractional differential equations, sufficient criteria about outer-synchronization of the controlled fractional-order neural networks are derived for structure-dependent centralized data-sampling, state-dependent centralized data-sampling, and state-dependent decentralized data-sampling, respectively. A numerical example is also given to illustrate the superiority of theoretical results. |
| format | Article |
| id | doaj-art-6525cfe1516f47d5b6d9f0d5ae3c20fb |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-6525cfe1516f47d5b6d9f0d5ae3c20fb2025-02-03T06:13:42ZengWileyComplexity1076-27871099-05262017-01-01201710.1155/2017/62906466290646Centralized and Decentralized Data-Sampling Principles for Outer-Synchronization of Fractional-Order Neural NetworksJin-E Zhang0Hubei Normal University, Hubei 435002, ChinaThis paper aims to investigate the outer-synchronization of fractional-order neural networks. Using centralized and decentralized data-sampling principles and the theory of fractional differential equations, sufficient criteria about outer-synchronization of the controlled fractional-order neural networks are derived for structure-dependent centralized data-sampling, state-dependent centralized data-sampling, and state-dependent decentralized data-sampling, respectively. A numerical example is also given to illustrate the superiority of theoretical results.http://dx.doi.org/10.1155/2017/6290646 |
| spellingShingle | Jin-E Zhang Centralized and Decentralized Data-Sampling Principles for Outer-Synchronization of Fractional-Order Neural Networks Complexity |
| title | Centralized and Decentralized Data-Sampling Principles for Outer-Synchronization of Fractional-Order Neural Networks |
| title_full | Centralized and Decentralized Data-Sampling Principles for Outer-Synchronization of Fractional-Order Neural Networks |
| title_fullStr | Centralized and Decentralized Data-Sampling Principles for Outer-Synchronization of Fractional-Order Neural Networks |
| title_full_unstemmed | Centralized and Decentralized Data-Sampling Principles for Outer-Synchronization of Fractional-Order Neural Networks |
| title_short | Centralized and Decentralized Data-Sampling Principles for Outer-Synchronization of Fractional-Order Neural Networks |
| title_sort | centralized and decentralized data sampling principles for outer synchronization of fractional order neural networks |
| url | http://dx.doi.org/10.1155/2017/6290646 |
| work_keys_str_mv | AT jinezhang centralizedanddecentralizeddatasamplingprinciplesforoutersynchronizationoffractionalorderneuralnetworks |