DocumentCode
2205532
Title
Research on non-linearity rectification of sensor systems
Author
Chen, Junjie ; Huang, Weiyi
Author_Institution
Dept. of Instrum. Sci. & Eng., Southeast Univ., Nanjing
fYear
2004
fDate
25-25 June 2004
Firstpage
176
Lastpage
180
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Acquisition, 2004. Proceedings. International Conference on
Conference_Location
Hefei
Print_ISBN
0-7803-8629-9
Type
conf
DOI
10.1109/ICIA.2004.1373345
Filename
1373345
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