[1]琚新刚,郭海鸥,郭敏..基于径向基神经网络的乙醇气体检测仪仿真分析[J].郑州大学学报(工学版),2010,31(03):61-64.[doi:10.3969/j.issn.1671-6833.2010.03.016]
　Ju Xingang,Guo Haiou,Guo Min.Simulation analysis of ethanol gas detector based on radial basis neural network[J].Journal of Zhengzhou University (Engineering Science),2010,31(03):61-64.[doi:10.3969/j.issn.1671-6833.2010.03.016]
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基于径向基神经网络的乙醇气体检测仪仿真分析()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
31卷
期数:
2010年03期
页码:
61-64
栏目:
出版日期:
2010-03-01

文章信息/Info

Title:
Simulation analysis of ethanol gas detector based on radial basis neural network
作者:
琚新刚; 郭海鸥; 郭敏.
郑州大学物理工程学院,河南郑州450001;河南教育学院电路与系统重点学科,河南郑州450046, 河南教育学院电路与系统重点学科,河南郑州,450046, 郑州大学物理工程学院,河南郑州,450001
Author(s):
Ju Xingang; Guo Haiou; Guo Min
关键词:
径向基函数;  神经网络;  曲线拟合;  Matlab仿真
Keywords:
DOI:
10.3969/j.issn.1671-6833.2010.03.016
文献标志码:
A
摘要:
以乙醇气体检测仪的算法设计为例,采用径向基神经网络,对34组乙醇气体浓度检测实验取得的标定数据进行拟合,即在Matlab环境下,利用径向基函数进行网络设计、仿真分析.结果显示,基于径向基网络的算法数据存储量小,并具有较好的误差性能,满足系统的误差要求,同时,网络的训练时间短,收敛速度快.
Abstract:
Taking the algorithm design of ethanol gas detector as an example, the radial basis neural network was used to fit the calibration data obtained from 34 groups of ethanol gas concentration detection experiments, that is, the network design and simulation analysis were carried out by using the radial basis function in the Matlab environment. The results show that the algorithm based on radial base network has small data storage and good error performance, which meets the error requirements of the system, and the training time of the network is short and the convergence speed is fast.

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更新日期/Last Update: 1900-01-01