首页 | 本学科首页   官方微博 | 高级检索  
     

数据融合技术在集员辨识中的应用
引用本文:梁礼明,万孟森,李钟侠. 数据融合技术在集员辨识中的应用[J]. 南方冶金学院学报, 2010, 31(1): 47-50
作者姓名:梁礼明  万孟森  李钟侠
作者单位:江西理工大学机电工程学院,江西赣州341000
摘    要:集员估计算法是一种新型的、有效的系统估计方法,在控制领域越来越受到重视.通过多传感器数据融合的方法,可以减少单一传感器辨识目标的不确定性和模糊性,可以进一步提高辨识结果的准确性和精度.文中提出了一种新型的基于数据融合的集员估计算法可以用来减少各种检测误差带来的影响,提高辨识的速度和精度.得出一个更优的集员估计集.

关 键 词:数据融合  不确定性  集员辨识

Applications of Data Fusion to Set Membership Identification
LIANG Li-ming,WAN Meng-sen,LI Zhong-xia. Applications of Data Fusion to Set Membership Identification[J]. Journal of Southern Institute of Metallurgy, 2010, 31(1): 47-50
Authors:LIANG Li-ming  WAN Meng-sen  LI Zhong-xia
Affiliation:Faculty of Mechanical and Electronic Engineering/a>;Jiangxi University of Science and Technology/a>;Ganzhou 341000/a>;China
Abstract:Set membership estimation algorithm is a newand effective system estimation method,which is becoming increasingly important in the control area.Multisensor data fusion is introduced to obtain higher accuracy of target recognition.The accuracy will be improved further if quality of information sources is examined at first.Set Member-ship Identification is taken in this paper to decrease different errors from detecting.which helps improve the speed and accuracy of identification.
Keywords:data fusion  uncertainty  set membership identification  
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号