JUNJIE CHEN
Department of Instrument Science and Engineering, Southeast University, 2 Si Pai Lou, Nanjing, Jiangsu 210096, P. R. China
WEIYI HUANG
Department of Instrument Science and Engineering, Southeast University, 2 Si Pai Lou, Nanjing, Jiangsu 210096, P. R. China

Received 3 August 2004
Accepted 15 December 2004

Genetic neural network model of solving the problem of nonlinearity rectification of sensor systems, is put forward in the light of the shortcomings of least square and other conventional methods. And in theory the model is emphatically expounded. Computer simulations are presented to demonstrate that approximation accuracy of the model is far higher than the conventional least square method and the model possesses stronger robustness through adopting the methods in this paper. The research in the paper indicates that the model can also be used to realize nonlinearity rectification in other similar systems.

Sensor; genetic algorithm; BP neural network; nonlinear rectification; accuracy