Improved delay-probability-dependent results for stochastic neural networks with randomly occurring uncertainties and multiple delays
文献类型：期刊论文
| 作者 | Luo, Jinnan1; Tian, Wenhong1,2 ; Zhong, Shouming3; Shi, Kaibo4; Gu, Xian-Ming5; Wang, Wenqin6
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| 刊名 | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
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| 出版日期 | 2018 |
| 卷号 | 49期号:9页码:2039-2059 |
| 关键词 | Probability distribution stochastic neural networks randomly occurring uncertainties convex combination |
| ISSN号 | 0020-7721 |
| DOI | 10.1080/00207721.2018.1483044 |
| 英文摘要 | This study seeks to address the delay-probability-dependent stability problem for a new class of stochastic neural networks with randomly occurring uncertainties, neutral type delay, distributed delay and probability-distribution delay. The system not only includes the randomly occurring uncertainties of parameters (ROUPs) but also contains stochastic disturbances, which is not yet investigated in existing papers. First, several stochastic variables which obey Bernoulli distribution are introduced to describe the ROUPs, based on which a new model is built. Second, through fully considering the information on kinds of delays and utilising general delay-partitioning method, an improved Lyapunov-Krasovskii function (LKF) is constructed. Combining Ito's differential formula, general bounding, free-weighting matrix and stochastic methods, a new delay-probability-dependent robustly mean square stable criterion is formulated in terms of linear matrix inequality. Finally, two numerical examples are given to demonstrate the effectiveness of the proposed results. |
| WOS研究方向 | Automation & Control Systems ; Computer Science ; Operations Research & Management Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000442628300016 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/6603]  |
| 专题 | 大数据挖掘及应用中心 |
| 通讯作者 | Luo, Jinnan; Tian, Wenhong |
| 作者单位 | 1.Univ Elect Sci & Technol China, Sch Informat & Software Engn, Chengdu 611731, Sichuan, Peoples R China 2.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing, Peoples R China 3.Univ Elect Sci & Technol China, Sch Math Sci, Chengdu, Sichuan, Peoples R China 4.Chengdu Univ, Sch Informat Sci & Engn, Chengdu, Sichuan, Peoples R China 5.Southwestern Univ Finance & Econ, Inst Math, Sch Econ Math, Chengdu, Sichuan, Peoples R China 6.Tianjin Polytech Univ, Sch Sci, Tianjin, Peoples R China |
| 推荐引用方式 GB/T 7714 | Luo, Jinnan,Tian, Wenhong,Zhong, Shouming,et al. Improved delay-probability-dependent results for stochastic neural networks with randomly occurring uncertainties and multiple delays[J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE,2018,49(9):2039-2059. |
| APA | Luo, Jinnan,Tian, Wenhong,Zhong, Shouming,Shi, Kaibo,Gu, Xian-Ming,&Wang, Wenqin.(2018).Improved delay-probability-dependent results for stochastic neural networks with randomly occurring uncertainties and multiple delays.INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE,49(9),2039-2059. |
| MLA | Luo, Jinnan,et al."Improved delay-probability-dependent results for stochastic neural networks with randomly occurring uncertainties and multiple delays".INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 49.9(2018):2039-2059. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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