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《Journal of Transducer Technology》 2003-06
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Adaptive partition method of improving sensor's nonlin ear using neural networks

ZHU Qingbao(Dept of Computer Sci,Nanjing Normal University, Nanjing 210097,China)  
A method that the inverse function of sensor's characteristic is identified with adaptive partition using neural netw orks.Using this method,the inverse function of sensor's characteristic can be partitioned into many intervals with adaptive method according to requis ition of learning accuracy using BP neural networks,and the interval function is learned and identified in the each interval respectively using a BP neural net work,after that,the each BP neural network replace the corresponding inverse fun ction in the each interval,and the sensor characteristics linearization are real ized.The results of simulations and application have shown that the nonlinear er rors of the sensor are decreased nine tenths using this method.
【Fund】: 江苏省教育厅自然科学基金资助项目(2001SXXTSJB111)
【CateGory Index】: TP212;TP183
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1 LU Zhi-yuan, ZHOU Yong-jun, LI Wei-jun(Coll of Elct Engin,Xidian University,Xi’an 710071,China);Study on method of nonlinear errors correction of sensor using BP neural network[J];Journal of Transducer Technology;2005-02
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7 ZHANG Yonghuai, LIU Junhua (Xi′an Jiaotong University, Xi′an 710049, P.R.China);Improvement of Sensor′s Performance by Using BP Neutral Network and It′s New Algorithms[J];Journal of Transcluction Technology;2002-03
8 CHEN Min1; MA Li2(1.Dept of Control Sci and Engin, Nanjing Normal University, Nanjing 210042,China;2.No 49th Research Institute,China Electronics Technology Group Corporation,Harbin 150001,China);Fitting way of sensor characteristic[J];Journal of Transducer Technology;2003-01
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【Secondary References】
Chinese Journal Full-text Database 2 Hits
1 DIAO Xiu-mu1,2(1.Department of Information,Ocean University of China,Qingdao 266071,China;2.Department of Information and control Engineering,Weifang University,Weifang 261061,China);Research of Non-linear Correction of Sensor Based on GRNN[J];Journal of Chongqing Institute of Technology(Natural Science);2008-10
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