Multisensor Data Fusion-Based Study on Set Membership Identification for the Intelligent Measurement System

被引：0

作者：

Liang, Liming ^{[1
]}

Wan, Mengsen ^{[1
]}

Li, Zhongxia ^{[1
]}

机构：

[1] Jiangxi Univ Sci & Technol, Sch Mech & Elect Engn, Ganzhou 341000, Jiangxi, Peoples R China

来源：

EBM 2010: INTERNATIONAL CONFERENCE ON ENGINEERING AND BUSINESS MANAGEMENT, VOLS 1-8 | 2010年

关键词：

multisensor; data fusion; uncertainly; set membership identification;

D O I：

暂无

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

Multisensor data fusion is introduced to decrease the uncertainty and fuzzyness of target recognition by single sensor. Using multisensor data fusion to evaluate information sources can the veracity and accuracy be improved further. Set Membership Identification based on multisensor data fusionis was put forward to reduce the effect of noise, and so to improve the precision of identification. The emulate results indicated that multisensor data fusion is feasible and effective.

引用

页码：5937 / 5940

页数：4

共 9 条

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