Delay-coupled fractional order complex Cohen-Grossberg neural networks under parameter uncertainty: Synchronization stability criteria
This paper inspects the issues of synchronization stability and robust synchronization stability for fractional order coupled complex interconnected Cohen-Grossberg neural networks under linear coupling delays. For investigation of synchronization stability results, the comparison theorem for multip...
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AIMS Press
2021-01-01
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Online Access: | http://www.aimspress.com/article/doi/10.3934/math.2021172?viewType=HTML |
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author | Pratap Anbalagan Evren Hincal Raja Ramachandran Dumitru Baleanu Jinde Cao Chuangxia Huang Michal Niezabitowski |
author_facet | Pratap Anbalagan Evren Hincal Raja Ramachandran Dumitru Baleanu Jinde Cao Chuangxia Huang Michal Niezabitowski |
author_sort | Pratap Anbalagan |
collection | DOAJ |
description | This paper inspects the issues of synchronization stability and robust synchronization stability for fractional order coupled complex interconnected Cohen-Grossberg neural networks under linear coupling delays. For investigation of synchronization stability results, the comparison theorem for multiple delayed fractional order linear system is derived at first. Then, by means of given fractional comparison principle, some inequality methods, Kronecker product technique and classical Lyapunov-functional, several asymptotical synchronization stability criteria are addressed in the voice of linear matrix inequality (LMI) for the proposed model. Moreover, when parameter uncertainty exists, we also the investigate on the robust synchronization stability criteria for complex structure on linear coupling delayed Cohen-Grossberg type neural networks. At last, the validity of the proposed analytical results are performed by two computer simulations. |
first_indexed | 2024-12-17T05:46:51Z |
format | Article |
id | doaj.art-c0dd6f0af6fe4b8eb31047757db32e3c |
institution | Directory Open Access Journal |
issn | 2473-6988 |
language | English |
last_indexed | 2024-12-17T05:46:51Z |
publishDate | 2021-01-01 |
publisher | AIMS Press |
record_format | Article |
series | AIMS Mathematics |
spelling | doaj.art-c0dd6f0af6fe4b8eb31047757db32e3c2022-12-21T22:01:17ZengAIMS PressAIMS Mathematics2473-69882021-01-016328442873Delay-coupled fractional order complex Cohen-Grossberg neural networks under parameter uncertainty: Synchronization stability criteriaPratap Anbalagan0Evren Hincal1Raja Ramachandran2Dumitru Baleanu3Jinde Cao4Chuangxia Huang5Michal Niezabitowski61. Department of Mathematics, Near East University TRNC, Mersin 10, Turkey1. Department of Mathematics, Near East University TRNC, Mersin 10, Turkey2. Ramanujan Centre for Higher Mathematics, Alagappa University, Karaikudi-630 004, India3. Department of Mathematics, Cankaya University, Ankara 06530, Turkey4. School of Mathematics, Southeast University, Nanjing 210096, China, and Yonsei Frontier Lab, Yonsei University, Seoul 03722, South Korea5. Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering, Changsha University of Science and Technology, Changsha, 410114, China6. Faculty of Automatic Control, Electronics and Computer Science, Department of Automatic Control, and Robotics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, PolandThis paper inspects the issues of synchronization stability and robust synchronization stability for fractional order coupled complex interconnected Cohen-Grossberg neural networks under linear coupling delays. For investigation of synchronization stability results, the comparison theorem for multiple delayed fractional order linear system is derived at first. Then, by means of given fractional comparison principle, some inequality methods, Kronecker product technique and classical Lyapunov-functional, several asymptotical synchronization stability criteria are addressed in the voice of linear matrix inequality (LMI) for the proposed model. Moreover, when parameter uncertainty exists, we also the investigate on the robust synchronization stability criteria for complex structure on linear coupling delayed Cohen-Grossberg type neural networks. At last, the validity of the proposed analytical results are performed by two computer simulations.http://www.aimspress.com/article/doi/10.3934/math.2021172?viewType=HTMLsynchronization stabilityfractional ordercomplex coupled cohen-grossberg neural networkskronecker productlinear coupling delay |
spellingShingle | Pratap Anbalagan Evren Hincal Raja Ramachandran Dumitru Baleanu Jinde Cao Chuangxia Huang Michal Niezabitowski Delay-coupled fractional order complex Cohen-Grossberg neural networks under parameter uncertainty: Synchronization stability criteria AIMS Mathematics synchronization stability fractional order complex coupled cohen-grossberg neural networks kronecker product linear coupling delay |
title | Delay-coupled fractional order complex Cohen-Grossberg neural networks under parameter uncertainty: Synchronization stability criteria |
title_full | Delay-coupled fractional order complex Cohen-Grossberg neural networks under parameter uncertainty: Synchronization stability criteria |
title_fullStr | Delay-coupled fractional order complex Cohen-Grossberg neural networks under parameter uncertainty: Synchronization stability criteria |
title_full_unstemmed | Delay-coupled fractional order complex Cohen-Grossberg neural networks under parameter uncertainty: Synchronization stability criteria |
title_short | Delay-coupled fractional order complex Cohen-Grossberg neural networks under parameter uncertainty: Synchronization stability criteria |
title_sort | delay coupled fractional order complex cohen grossberg neural networks under parameter uncertainty synchronization stability criteria |
topic | synchronization stability fractional order complex coupled cohen-grossberg neural networks kronecker product linear coupling delay |
url | http://www.aimspress.com/article/doi/10.3934/math.2021172?viewType=HTML |
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