Intermittent Control for Synchronization of Markov Jump Inertial Neural Networks with Reaction–Diffusion Terms via Non-reduced-Order Method
This paper concentrates on designing an aperiodically intermittent controller for synchronization of Markov jump inertial neural networks (MJINNs) with reaction–diffusion terms. Unlike the traditional reduced-order variable substitution method, the synchronization for MJINNs is studied directly usin...
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| Published in | Circuits, systems, and signal processing Vol. 42; no. 1; pp. 199 - 215 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.01.2023
Springer Nature B.V |
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| Abstract | This paper concentrates on designing an aperiodically intermittent controller for synchronization of Markov jump inertial neural networks (MJINNs) with reaction–diffusion terms. Unlike the traditional reduced-order variable substitution method, the synchronization for MJINNs is studied directly using a non-reduced-order method. Besides, an aperiodic intermittent controller with spatially sampled data, which is intermittent in time and sampled data in space, is constructed under the consideration of the limited communication bandwidth. Furthermore, based on the Lyapunov direct method and several inequality techniques, the synchronization criteria of MJINNs under the proposed controller are derived. Finally, the proposed approach’s effectiveness is illustrated by using a numerical example. |
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| AbstractList | This paper concentrates on designing an aperiodically intermittent controller for synchronization of Markov jump inertial neural networks (MJINNs) with reaction–diffusion terms. Unlike the traditional reduced-order variable substitution method, the synchronization for MJINNs is studied directly using a non-reduced-order method. Besides, an aperiodic intermittent controller with spatially sampled data, which is intermittent in time and sampled data in space, is constructed under the consideration of the limited communication bandwidth. Furthermore, based on the Lyapunov direct method and several inequality techniques, the synchronization criteria of MJINNs under the proposed controller are derived. Finally, the proposed approach’s effectiveness is illustrated by using a numerical example. |
| Author | Hu, Dongxiao Li, Xingru Ma, Jianwei Song, Xiaona |
| Author_xml | – sequence: 1 givenname: Dongxiao surname: Hu fullname: Hu, Dongxiao organization: School of Information Engineering, Henan University of Science and Technology – sequence: 2 givenname: Xiaona orcidid: 0000-0001-8476-5112 surname: Song fullname: Song, Xiaona email: xiaona_97@163.com organization: School of Information Engineering, Henan University of Science and Technology – sequence: 3 givenname: Xingru surname: Li fullname: Li, Xingru organization: School of Information Engineering, Henan University of Science and Technology – sequence: 4 givenname: Jianwei surname: Ma fullname: Ma, Jianwei organization: School of Information Engineering, Henan University of Science and Technology |
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| CitedBy_id | crossref_primary_10_1002_acs_3856 crossref_primary_10_1177_09596518241246812 crossref_primary_10_1016_j_neunet_2024_106671 crossref_primary_10_3390_math12121911 crossref_primary_10_1007_s12190_024_02234_w |
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| Keywords | Aperiodically intermittent controller Spatially sampled data Synchronization Reaction–diffusion Markov jump inertial neural networks Non-reduced order |
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| SubjectTerms | Circuits Circuits and Systems Controllers Diffusion Electrical Engineering Electronics and Microelectronics Engineering Instrumentation Liapunov direct method Methods Neural networks Sampled data Signal processing Signal,Image and Speech Processing Substitution reactions Synchronism |
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| Title | Intermittent Control for Synchronization of Markov Jump Inertial Neural Networks with Reaction–Diffusion Terms via Non-reduced-Order Method |
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