Computational Neural Dynamics Model for Time-Variant Constrained Nonlinear Optimization Applied to Winner-Take-All Operation
文献类型：期刊论文
| 作者 | Liu, Mei1,2,3; Zhang, Xiaoyan1,2,3; Shang, Mingsheng3
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| 刊名 | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
 |
| 出版日期 | 2022-09-01 |
| 卷号 | 18期号:9页码:5936-5948 |
| 关键词 | Optimization Mathematical models Computational modeling Neural networks Numerical models Informatics Vehicle dynamics Equality and inequality constraints noise-suppressing discrete-time neural dynamics (NSDTND) model time-variant nonlinear optimization |
| ISSN号 | 1551-3203 |
| DOI | 10.1109/TII.2021.3138794 |
| 通讯作者 | Shang, Mingsheng(msshang@cigit.ac.cn) |
| 英文摘要 | Although time-variant nonlinear optimization with equality and inequality constraints (TVNOEIC) is a widespread problem in real life, the research on this issue is much less than the time-invariant one. Large lagging errors may not be inevitable if the traditional models designed for time-invariant optimizations are exploited to time-variant ones. To eliminate the lagging errors, models for handling time-variant optimization problems are urgently required. Recently, neural networks and the related neural dynamics approaches have witnessed rapid developments and made significant contributions to the online solution of various problems. On this basis, a noise-suppressing discrete-time neural dynamics (NSDTND) model is proposed in this article for solving the TVNOEIC problem. Theoretical analysis is presented to prove that the residual error of the proposed model is tiny enough to estimate the actual solution even in the presence of noise perturbation. In addition, numerical simulations, including an application on winner-take-all operation, are provided to further demonstrate the effectiveness and robustness of the proposed NSDTND model. |
| 资助项目 | National Natural Science Foundation of China[62176109] ; National Natural Science Foundation of China[62072429] ; Natural Science Foundation of Chongqing, China[cstc2020jcyj-zdxmX0028] ; Chinese Academy of Sciences Light of West China Program ; Natural Science Foundation of Gansu Province[21JR7RA531] ; Natural Science Foundation of Gansu Province[20JR10RA639] ; Key Cooperation Project of Chongqing Municipal Education Commission[HZ2021017] ; Key Cooperation Project of Chongqing Municipal Education Commission[HZ2021008] ; Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province[2021-Z-003] ; Fundamental Research Funds for the Central Universities[lzujbky-2021-65] ; Education Department of Gansu Province[2021CXZX-122] |
| WOS研究方向 | Automation & Control Systems ; Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000811603400024 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/16187]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 通讯作者 | Shang, Mingsheng |
| 作者单位 | 1.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China 2.State Key Lab Tibetan Intelligent Informat Proc &, Xining 810016, Peoples R China 3.Chinese Acad Sci, Chongqing Key Lab Big Data & Intelligent Comp, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Mei,Zhang, Xiaoyan,Shang, Mingsheng. Computational Neural Dynamics Model for Time-Variant Constrained Nonlinear Optimization Applied to Winner-Take-All Operation[J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,2022,18(9):5936-5948. |
| APA | Liu, Mei,Zhang, Xiaoyan,&Shang, Mingsheng.(2022).Computational Neural Dynamics Model for Time-Variant Constrained Nonlinear Optimization Applied to Winner-Take-All Operation.IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,18(9),5936-5948. |
| MLA | Liu, Mei,et al."Computational Neural Dynamics Model for Time-Variant Constrained Nonlinear Optimization Applied to Winner-Take-All Operation".IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 18.9(2022):5936-5948. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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