Global Exponential Stability of a Class of Memristor-Based RNN and Its Application to Design Stable Voltage Circuits
In this article, we study the global exponential stability of the equilibrium point for a class of memristor-based recurrent neural networks (MRNNs). The MRNNs are based on a realistic memristor model and can be implemented by a very large scale of integration circuits. By introducing a proper Lyapu...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-04-01
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| Series: | Frontiers in Energy Research |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2022.887769/full |
| _version_ | 1818275091913375744 |
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| author | Zhao Yao Zhao Yao Yingshun Li |
| author_facet | Zhao Yao Zhao Yao Yingshun Li |
| author_sort | Zhao Yao |
| collection | DOAJ |
| description | In this article, we study the global exponential stability of the equilibrium point for a class of memristor-based recurrent neural networks (MRNNs). The MRNNs are based on a realistic memristor model and can be implemented by a very large scale of integration circuits. By introducing a proper Lyapunov functional, it is proved that the equilibrium point of the MRNN is globally exponentially stable under two less conservative assumptions. Furthermore, an algorithm is proposed for the design of MRNN-based circuits with stable voltages. Finally, an illustration example is performed to show the validation of the proposed theoretical results; an MRNN-based circuit with stable voltages is designed according to the proposed algorithm. |
| first_indexed | 2024-12-12T22:24:15Z |
| format | Article |
| id | doaj.art-8f6e31bb57d34cba8499e87556437860 |
| institution | Directory Open Access Journal |
| issn | 2296-598X |
| language | English |
| last_indexed | 2024-12-12T22:24:15Z |
| publishDate | 2022-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj.art-8f6e31bb57d34cba8499e875564378602022-12-22T00:09:49ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2022-04-011010.3389/fenrg.2022.887769887769Global Exponential Stability of a Class of Memristor-Based RNN and Its Application to Design Stable Voltage CircuitsZhao Yao0Zhao Yao1Yingshun Li 2Army Academy of Armored Forces, Changchun, ChinaSchool of Control Science and Engineering, Dalian University of Technology, Dalian, ChinaSchool of Control Science and Engineering, Dalian University of Technology, Dalian, ChinaIn this article, we study the global exponential stability of the equilibrium point for a class of memristor-based recurrent neural networks (MRNNs). The MRNNs are based on a realistic memristor model and can be implemented by a very large scale of integration circuits. By introducing a proper Lyapunov functional, it is proved that the equilibrium point of the MRNN is globally exponentially stable under two less conservative assumptions. Furthermore, an algorithm is proposed for the design of MRNN-based circuits with stable voltages. Finally, an illustration example is performed to show the validation of the proposed theoretical results; an MRNN-based circuit with stable voltages is designed according to the proposed algorithm.https://www.frontiersin.org/articles/10.3389/fenrg.2022.887769/fullmemristorvoltagecircuitrecurrent neural networkstability |
| spellingShingle | Zhao Yao Zhao Yao Yingshun Li Global Exponential Stability of a Class of Memristor-Based RNN and Its Application to Design Stable Voltage Circuits Frontiers in Energy Research memristor voltage circuit recurrent neural network stability |
| title | Global Exponential Stability of a Class of Memristor-Based RNN and Its Application to Design Stable Voltage Circuits |
| title_full | Global Exponential Stability of a Class of Memristor-Based RNN and Its Application to Design Stable Voltage Circuits |
| title_fullStr | Global Exponential Stability of a Class of Memristor-Based RNN and Its Application to Design Stable Voltage Circuits |
| title_full_unstemmed | Global Exponential Stability of a Class of Memristor-Based RNN and Its Application to Design Stable Voltage Circuits |
| title_short | Global Exponential Stability of a Class of Memristor-Based RNN and Its Application to Design Stable Voltage Circuits |
| title_sort | global exponential stability of a class of memristor based rnn and its application to design stable voltage circuits |
| topic | memristor voltage circuit recurrent neural network stability |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2022.887769/full |
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