| 基于人工神经网络的传感器非线性拟合方法的研究 |
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| 引用本文： | 张丹,于朝民,付永杰.基于人工神经网络的传感器非线性拟合方法的研究[J].工业计量,2004,14(5):31-33. |
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| 作者姓名： | 张丹 于朝民 付永杰 |
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| 作者单位： | 中国人民解放军92493部队,辽宁,葫芦岛,125001;中国人民解放军92493部队,辽宁,葫芦岛,125001;中国人民解放军92493部队,辽宁,葫芦岛,125001 |
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| 摘 要： | 人工神经网络具有以任意精度逼近任何非线性连续函数的能力。文章分别用BP网络、RBF网络对传感器的非线性作高精度拟合。仿真结果表明，三层BP网络和RBF网络能够满足工程实际中一维数据拟合的要求，网络具有良好的泛化能力。
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| 关 键 词： | BP网络 RBF网络 传感器 非线性拟合 |
| 文章编号： | 1002-1183(2004)05-0031-03 |
| 修稿时间： | 2003年12月5日 |
Study on nonlinear fitting method of transducer based on artificial neural network |
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| ZHANG Dan,YU Chao-min,FU Yong-jie.Study on nonlinear fitting method of transducer based on artificial neural network[J].Industrial Measurement,2004,14(5):31-33. |
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| Authors: | ZHANG Dan YU Chao-min FU Yong-jie |
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| Abstract: | The artificial neural network can approximate any nonlinear function at arbitrary precision.This paper uses back propagation and RBF network to approximate the nonlinear of transducer at high precise.The approved BP algorithm speeds up learning.The simulation result shows three-1ayered BP network and RFB network can meet with one dimension curve fining in engineering practice.The network have a great generalization ability. |
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| Keywords: | BP network RBF network transducer nonlinear fitting |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
