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Robustness analysis of a hybrid of recursive neural dynamics for online matrix inversion
文献类型：期刊论文
| 作者 | Chen, Ke; Yi, Chenfu |
| 刊名 | APPLIED MATHEMATICS AND COMPUTATION
 |
| 出版日期 | 2016 |
| 英文摘要 | Encouraged by superior convergence performance achieved by a recently proposed hybrid of recursive neural dynamics for online matrix inversion, we investigate its robustness properties in this paper when there exists large rnodel implementation errors. Theoretical analysis shows that the perturbed dynamic system is still global stable with the tight steady-state bound of solution error estimated. Moreover, this paper analyses global exponential convergence rate and finite convergence time of such a hybrid dynamical model to a relatively loose solution error bound. Computer simulation results substantiate our analysis on the perturbed hybrid neural dynamics for online matrix inversion when having large implementation errors. (C) 2015 Elsevier Inc. All rights reserved. |
| 收录类别 | SCI |
| 原文出处 | http://www.sciencedirect.com/science/article/pii/S0096300315013685 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/10390]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 作者单位 | APPLIED MATHEMATICS AND COMPUTATION |
| 推荐引用方式 GB/T 7714 | Chen, Ke,Yi, Chenfu. Robustness analysis of a hybrid of recursive neural dynamics for online matrix inversion[J]. APPLIED MATHEMATICS AND COMPUTATION,2016. |
| APA | Chen, Ke,&Yi, Chenfu.(2016).Robustness analysis of a hybrid of recursive neural dynamics for online matrix inversion.APPLIED MATHEMATICS AND COMPUTATION. |
| MLA | Chen, Ke,et al."Robustness analysis of a hybrid of recursive neural dynamics for online matrix inversion".APPLIED MATHEMATICS AND COMPUTATION (2016). |
入库方式： OAI收割
来源：深圳先进技术研究院
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