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Study of Fitting Methods of Giant Magneto-Impedance Sensors’ Output Signals

As magnetic field varies greatly under complex environment, it is difficult for GMI sensor to adapt. On basis of analyzing the curve of GMI effect, curve fitting methods with polynomial, sum of sine functions and the BP neural network are studied to find the best one to fit the sensors’ outputs. When the best one is acted as model of the GMI sensor for measurement, the measurement precision can be effectively improved and the sensors' range can be greatly expanded.