Stability Analysis Based on Caputo-Type Fractional-Order Quantum Neural Networks
In this paper, a quantum neural network with multilayer activation function is proposed by using multilayer Sigmoid function superposition and learning algorithm to adjust quantum interval. On this basis, the quasiuniform stability of fractional quantum neural networks with mixed delays is studied....
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Function Spaces |
| Online Access: | http://dx.doi.org/10.1155/2021/3820092 |
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| _version_ | 1849308949987196928 |
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| author | Yumin Dong Xiang Li Wei Liao Dong Hou |
| author_facet | Yumin Dong Xiang Li Wei Liao Dong Hou |
| author_sort | Yumin Dong |
| collection | DOAJ |
| description | In this paper, a quantum neural network with multilayer activation function is proposed by using multilayer Sigmoid function superposition and learning algorithm to adjust quantum interval. On this basis, the quasiuniform stability of fractional quantum neural networks with mixed delays is studied. According to the order of two different cases, the conditions of quasi uniform stability of networks are given by using the techniques of linear matrix inequality analysis, and the sufficiency of the conditions is proved. Finally, the feasibility of the conclusion is verified by experiments. |
| format | Article |
| id | doaj-art-0bbf33e5710f450787b1b2ab004b192f |
| institution | Kabale University |
| issn | 2314-8896 2314-8888 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Function Spaces |
| spelling | doaj-art-0bbf33e5710f450787b1b2ab004b192f2025-08-20T03:54:19ZengWileyJournal of Function Spaces2314-88962314-88882021-01-01202110.1155/2021/38200923820092Stability Analysis Based on Caputo-Type Fractional-Order Quantum Neural NetworksYumin Dong0Xiang Li1Wei Liao2Dong Hou3College of Computer and Information Science, Chongqing Normal University, Chongqing 401331, ChinaCollege of Computer and Information Science, Chongqing Normal University, Chongqing 401331, ChinaCollege of Computer and Information Science, Chongqing Normal University, Chongqing 401331, ChinaCollege of Computer and Information Science, Chongqing Normal University, Chongqing 401331, ChinaIn this paper, a quantum neural network with multilayer activation function is proposed by using multilayer Sigmoid function superposition and learning algorithm to adjust quantum interval. On this basis, the quasiuniform stability of fractional quantum neural networks with mixed delays is studied. According to the order of two different cases, the conditions of quasi uniform stability of networks are given by using the techniques of linear matrix inequality analysis, and the sufficiency of the conditions is proved. Finally, the feasibility of the conclusion is verified by experiments.http://dx.doi.org/10.1155/2021/3820092 |
| spellingShingle | Yumin Dong Xiang Li Wei Liao Dong Hou Stability Analysis Based on Caputo-Type Fractional-Order Quantum Neural Networks Journal of Function Spaces |
| title | Stability Analysis Based on Caputo-Type Fractional-Order Quantum Neural Networks |
| title_full | Stability Analysis Based on Caputo-Type Fractional-Order Quantum Neural Networks |
| title_fullStr | Stability Analysis Based on Caputo-Type Fractional-Order Quantum Neural Networks |
| title_full_unstemmed | Stability Analysis Based on Caputo-Type Fractional-Order Quantum Neural Networks |
| title_short | Stability Analysis Based on Caputo-Type Fractional-Order Quantum Neural Networks |
| title_sort | stability analysis based on caputo type fractional order quantum neural networks |
| url | http://dx.doi.org/10.1155/2021/3820092 |
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