高技术通讯（英文版）2002，Vol.8Issue(2)：83-86,4.
Application of New Type BP Neural Networks for Magnetic Measurement
Application of New Type BP Neural Networks for Magnetic Measurement
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作者信息
- 1. Dept. of Automatic Measurement and Control, School of Computer Science and Engineering,Harbin Institute of Technology, Harbin 150001, P.R.China;Dept. of Automatic Measurement and Control, School of Computer Science and Engineering,Harbin Institute of Technology, Harbin 150001, P.R.China;Dept. of Electronic Engineering, University of Tokushima, Japan;Dept. of Automatic Measurement and Control, School of Computer Science and Engineering,Harbin Institute of Technology, Harbin 150001, P.R.China
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摘要
Abstract
Magnetic measurement is a typical inverse problem in Biomedical field. In this kind of problem we always need to locate the positions and moments of one or more magnetic dipoles. Although using the traditional methods to solve this kind of inverse problem has all kinds of shortcomings, BPNN (Back Propagation Neural Networks) method can be used to solve this typical inverse problem fast enough for real time measurement. In the traditional BPNN method, gradient descent search method is performed for error propagation. In this paper the authors propose a new algorithm that Newton method is performed for error propagation. For the cost function is highly nonconvex in the magnetic measurement problem, the new kind of BPNN can get convergent results quickly and precisely. A simulation result for this method is also presented. 关键词
magnetic measurement/BP neural network/gradient method/Newton-Gauss methodKey words
magnetic measurement/BP neural network/gradient method/Newton-Gauss method分类
信息技术与安全科学引用本文复制引用
..Application of New Type BP Neural Networks for Magnetic Measurement[J].高技术通讯（英文版）,2002,8(2):83-86,4.
