The algorithm of neural networks on the initial value problems in ordinary differential equations

被引：0

作者：

Xu Li-Ying ^{[1
]}

Wen Hui ^{[1
]}

Zeng Zhe-zhao ^{[1
]}

机构：

[1] Changsha Univ Sci & Technol, Changsha 410077, Hunan, Peoples R China

来源：

ICIEA 2007: 2ND IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-4, PROCEEDINGS | 2007年

关键词：

neural network; cosine basis functions; ordinary differential equations; convergence theorem;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

A new method for solving Initial Value problems in Ordinary Differential Equations (ODEs) is proposed in this paper. The algorithm of neural networks based on the cosine basis functions is studied in detail. The convergence theorem of neural networks algorithm is given and proved. The algorithm is validated by the simulation examples of ODEs. The results show the proposed approach is more precise than modified Enter Method and Henn's Method.

引用

页码：813 / 816

页数：4

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