Stability analysis for μ-p.a.a. solutions of MAM neural network with neuron gains
The work considers the μ-p.a.a. (measure-pseudo almost automorphic) solutions of MAM neural network with neuron gains. By using the properties of μ-p.a.a. functions, inequality technique and Banach contraction mapping principle, some sufficient conditions are obtained to ensure the existence and the...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824012778 |
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| _version_ | 1825206950526189568 |
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| author | Feng-Xia Zheng Ni Zeng Chuan-Yun Gu |
| author_facet | Feng-Xia Zheng Ni Zeng Chuan-Yun Gu |
| author_sort | Feng-Xia Zheng |
| collection | DOAJ |
| description | The work considers the μ-p.a.a. (measure-pseudo almost automorphic) solutions of MAM neural network with neuron gains. By using the properties of μ-p.a.a. functions, inequality technique and Banach contraction mapping principle, some sufficient conditions are obtained to ensure the existence and the global exponential stability of a unique μ-p.a.a. solution of MAM neural network with neuron gains. Moreover, some numerical examples are given to illustrate our main results. |
| format | Article |
| id | doaj-art-63af11f393114666bfd4bd4319c99f69 |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-63af11f393114666bfd4bd4319c99f692025-02-07T04:46:56ZengElsevierAlexandria Engineering Journal1110-01682025-02-01113306317Stability analysis for μ-p.a.a. solutions of MAM neural network with neuron gainsFeng-Xia Zheng0Ni Zeng1Chuan-Yun Gu2School of Science, Xihua University, Chengdu, Sichuan 610039, PR ChinaSchool of Science, Xihua University, Chengdu, Sichuan 610039, PR ChinaSchool of Mathematics, Sichuan Institute of Arts and Science, Dazhou, Sichuan 635000, PR China; Corresponding author.The work considers the μ-p.a.a. (measure-pseudo almost automorphic) solutions of MAM neural network with neuron gains. By using the properties of μ-p.a.a. functions, inequality technique and Banach contraction mapping principle, some sufficient conditions are obtained to ensure the existence and the global exponential stability of a unique μ-p.a.a. solution of MAM neural network with neuron gains. Moreover, some numerical examples are given to illustrate our main results.http://www.sciencedirect.com/science/article/pii/S1110016824012778Banach fixed point theoremMAM neural networkGlobally exponential stabilityMeasure-pseudo almost automorphicNeuron gains |
| spellingShingle | Feng-Xia Zheng Ni Zeng Chuan-Yun Gu Stability analysis for μ-p.a.a. solutions of MAM neural network with neuron gains Alexandria Engineering Journal Banach fixed point theorem MAM neural network Globally exponential stability Measure-pseudo almost automorphic Neuron gains |
| title | Stability analysis for μ-p.a.a. solutions of MAM neural network with neuron gains |
| title_full | Stability analysis for μ-p.a.a. solutions of MAM neural network with neuron gains |
| title_fullStr | Stability analysis for μ-p.a.a. solutions of MAM neural network with neuron gains |
| title_full_unstemmed | Stability analysis for μ-p.a.a. solutions of MAM neural network with neuron gains |
| title_short | Stability analysis for μ-p.a.a. solutions of MAM neural network with neuron gains |
| title_sort | stability analysis for μ p a a solutions of mam neural network with neuron gains |
| topic | Banach fixed point theorem MAM neural network Globally exponential stability Measure-pseudo almost automorphic Neuron gains |
| url | http://www.sciencedirect.com/science/article/pii/S1110016824012778 |
| work_keys_str_mv | AT fengxiazheng stabilityanalysisformpaasolutionsofmamneuralnetworkwithneurongains AT nizeng stabilityanalysisformpaasolutionsofmamneuralnetworkwithneurongains AT chuanyungu stabilityanalysisformpaasolutionsofmamneuralnetworkwithneurongains |