Research on non-linearity rectification of sensor systems

Junjie Chen, Weiyi Huang
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Abstract

Genetic neural network model of solving the problems on nonlinearity rectification of sensor systems, was put forward, for the shortcoming of least square and other conventional methods. Computer simulations are given to demonstrate that approximation accuracy of the model is far higher than least square method that are extensively applied conventionally and the model possesses stronger robustness through adopting the standpoints and methods in this paper. And the research indicates that the model can be also used to realize nonlinearity rectification in other similar systems
传感器系统非线性整流研究
针对最小二乘法和其他传统方法的不足,提出了求解传感器系统非线性校正问题的遗传神经网络模型。计算机仿真结果表明,采用本文提出的观点和方法,模型的逼近精度远高于传统广泛应用的最小二乘法,模型具有更强的鲁棒性。研究表明,该模型也可用于其他类似系统的非线性校正
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