2008Microfabrication TechnologyRequires access

Characteristic Curve Fitting of the Hall Sensor Based on Cubic Splines Function

Liao Hai-sheng

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Abstract

In order to increase effectiveness to fitting the characteristic curve of the Hall sensor,the theory of the cubic splines functions were analyzed.In Matlab 6.5,the experiments with synthetical data of the UH-B curve of UGN3501U type was done.And a scheme for reduce the fitting points was proposed,which can cut down the cost and the worklod and has little effect to the relative errortoo.The experimental resluts illuminate that the fitting curve which reducing the fitting points with our method is also soomth and has high precision and little relative error in comparison with the original curve.As a result,the method is more valuable in theory and has strong practicability at the same time.

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What this paper is about

In order to increase effectiveness to fitting the characteristic curve of the Hall sensor,the theory of the cubic splines functions were analyzed.In Matlab 6.5,the experiments with synthetical data of the UH-B curve of UGN3501U type was done.And a scheme for reduce the fitting points was proposed,which can cut down the cost and the worklod and has little effect to the relative errortoo.The experimental resluts illuminate that the fitting curve which reducing the fitting points with our method is also soomth and has high precision and little relative error in comparison with the original curve.As a result,the method is more valuable in theory and has strong practicability at the same time.

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Available abstract

In order to increase effectiveness to fitting the characteristic curve of the Hall sensor,the theory of the cubic splines functions were analyzed.In Matlab 6.5,the experiments with synthetical data of the UH-B curve of UGN3501U type was done.And a scheme for reduce the fitting points was proposed,which can cut down the cost and the worklod and has little effect to the relative errortoo.The experimental resluts illuminate that the fitting curve which reducing the fitting points with our method is also soomth and has high precision and little relative error in comparison with the original curve.As a result,the method is more valuable in theory and has strong practicability at the same time.

Key concepts: Curve fitting, Function (biology), MATLAB, Approximation error, Cubic function, Mathematics, Data point, Mathematical analysis

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