A New Varying-Factor Finite-Time Recurrent Neural Network to Solve the Time-Varying Sylvester Equation Online
This paper presents a varying-parameter finite-time recurrent neural network, called a varying-factor finite-time recurrent neural network (VFFTRNN), which is able to solve the solution of the time-varying Sylvester equation online. The proposed neural network makes the matrix coefficients vary with...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/12/24/3891 |
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| author | Haoming Tan Junyun Wu Hongjie Guan Zhijun Zhang Ling Tao Qingmin Zhao Chunquan Li |
| author_facet | Haoming Tan Junyun Wu Hongjie Guan Zhijun Zhang Ling Tao Qingmin Zhao Chunquan Li |
| author_sort | Haoming Tan |
| collection | DOAJ |
| description | This paper presents a varying-parameter finite-time recurrent neural network, called a varying-factor finite-time recurrent neural network (VFFTRNN), which is able to solve the solution of the time-varying Sylvester equation online. The proposed neural network makes the matrix coefficients vary with time and can achieve convergence in a finite time. Apart from this, the performance of the network is better than traditional networks in terms of robustness. It is theoretically proved that the proposed neural network has super-exponential convergence performance. Simulation results demonstrate that this neural network has faster convergence speed and better robustness than the return to zero neural networks and can track the theoretical solution of the time-varying Sylvester equation effectively. |
| format | Article |
| id | doaj-art-0baf5c10488549608e1656b87d813b50 |
| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-0baf5c10488549608e1656b87d813b502024-12-27T14:37:55ZengMDPI AGMathematics2227-73902024-12-011224389110.3390/math12243891A New Varying-Factor Finite-Time Recurrent Neural Network to Solve the Time-Varying Sylvester Equation OnlineHaoming Tan0Junyun Wu1Hongjie Guan2Zhijun Zhang3Ling Tao4Qingmin Zhao5Chunquan Li6School of Electric and Electronic Enginnering, Shanghai University of Engineering Science, Shanghai 201620, ChinaSchool of Mathematics and Computer Sciences, Nanchang University, Nanchang 330031, ChinaSchool of Information Engineering, Nanchang University, Nanchang 330031, ChinaSchool of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, ChinaJiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction, Nanchang 330031, ChinaJiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction, Nanchang 330031, ChinaJiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction, Nanchang 330031, ChinaThis paper presents a varying-parameter finite-time recurrent neural network, called a varying-factor finite-time recurrent neural network (VFFTRNN), which is able to solve the solution of the time-varying Sylvester equation online. The proposed neural network makes the matrix coefficients vary with time and can achieve convergence in a finite time. Apart from this, the performance of the network is better than traditional networks in terms of robustness. It is theoretically proved that the proposed neural network has super-exponential convergence performance. Simulation results demonstrate that this neural network has faster convergence speed and better robustness than the return to zero neural networks and can track the theoretical solution of the time-varying Sylvester equation effectively.https://www.mdpi.com/2227-7390/12/24/3891recurrent neural network (RNN)finite timesuper-exponential convergence rate |
| spellingShingle | Haoming Tan Junyun Wu Hongjie Guan Zhijun Zhang Ling Tao Qingmin Zhao Chunquan Li A New Varying-Factor Finite-Time Recurrent Neural Network to Solve the Time-Varying Sylvester Equation Online Mathematics recurrent neural network (RNN) finite time super-exponential convergence rate |
| title | A New Varying-Factor Finite-Time Recurrent Neural Network to Solve the Time-Varying Sylvester Equation Online |
| title_full | A New Varying-Factor Finite-Time Recurrent Neural Network to Solve the Time-Varying Sylvester Equation Online |
| title_fullStr | A New Varying-Factor Finite-Time Recurrent Neural Network to Solve the Time-Varying Sylvester Equation Online |
| title_full_unstemmed | A New Varying-Factor Finite-Time Recurrent Neural Network to Solve the Time-Varying Sylvester Equation Online |
| title_short | A New Varying-Factor Finite-Time Recurrent Neural Network to Solve the Time-Varying Sylvester Equation Online |
| title_sort | new varying factor finite time recurrent neural network to solve the time varying sylvester equation online |
| topic | recurrent neural network (RNN) finite time super-exponential convergence rate |
| url | https://www.mdpi.com/2227-7390/12/24/3891 |
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