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中国科学院软件研究所
  
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朱庆保.用于传感器非线性误差校正的新颖神经网络.软件学报,1999,10(12):1298-1303
用于传感器非线性误差校正的新颖神经网络
A Novel CMAC Neural Network for Correcting the Sensor's Nonlinear Errors
投稿时间:1998-09-25  修订日期:1998-12-23
DOI:
中文关键词:  小脑模型神经网络,传感器,非线性误差,校正,仿真.
英文关键词:Cerebella model articulation controller (CMAC), sensor, nonlinear errors, correction, simulation.
基金项目:本文研究得到江苏省科委应用基础项目基金资助.
作者单位
朱庆保 南京师范大学计算机技术开发部,南京,210097 
摘要点击次数: 2690
全文下载次数: 2595
中文摘要:
      该文阐述了用神经网络校正传感系统非线性误差的原理和方法,提出了一种新颖的简化小脑模型神经网络(SCMAC)及其模型、算法与实现技术.模型、算法采用直接权地址映射技术,以训练样本的输入为地址,建立起输入与权重的关系.任意输入作为相近的权地址,即可找到对应的权,经过联想插补后可获得高精度输出.此外,采用磁盘文件存储、寻址权重等方法,避免了微机内存溢出,使得实现容易.最后给出了一个仿真实验.实验结果表明,用SCMAC校正后,可使传感器的非线性误差减少到近似为零.
英文摘要:
      In this paper, the principles and the methods for correcting the nonlinear errors of the sensor system with a neural network are shown, and a novel simplified cerebella model articulation controller (SCMAC), which includes its model, algorithm and realized techniques, is proposed. The direct weight address mapping techniques are used in this model and algorithm, and the relation between the inputs and the weights is established by taking the inputs of training samples as their weight address, and the corresponding weights are found for any inputs by taking it as similar weight address, and the accurate outputs are obtained by the associable insertion algorithm. In addition, the weights are stored and addressed in a magnetic disk file, therefore, the overflow of internal memory of microcomputer are avoided, and the SCMAC is easily realized. Finally, a simulation experiment is given and the results show that the nonlinear errors of the sensor system are decreased to approximate zero after correcting with a SCMAC.
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