Title :
Research on non-linearity rectification of sensor systems
Author :
Chen, Junjie ; Huang, Weiyi
Author_Institution :
Dept. of Instrum. Sci. & Eng., Southeast Univ., Nanjing
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
Keywords :
backpropagation; control systems; genetic algorithms; least mean squares methods; measurement systems; neural nets; rectification; sensors; BP neural network; genetic algorithm; genetic neural network model; least square methods; nonlinearity rectification; sensor systems; Computer simulation; Control systems; Genetic algorithms; Genetic engineering; Instruments; Least squares approximation; Least squares methods; Neural networks; Robustness; Sensor systems;
Conference_Titel :
Information Acquisition, 2004. Proceedings. International Conference on
Conference_Location :
Hefei
Print_ISBN :
0-7803-8629-9
DOI :
10.1109/ICIA.2004.1373345
