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DOI:
Journal of Software:1997.8(4):303-307

目标识别中信息融合的准则和方法
章新华,林良骥,王骥程
(浙江大学工业控制技术研究所,杭州,310027; 大连测控技术研究所,大连,116013)
CRITERIONS AND APPROACHES OF INFORMATION FUSION IN TARGET RECOGNITION
ZHANG Xinhua,LIN Liangji,WANG Jicheng
()
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    Revised:April 16, 1996
> 中文摘要: 本文用信息论的观点,给出了在设计单个分类器时使系统性能得以提高的条件,基于群组决策理论和模糊积分方法提出了一种多证据条件下进行信息融合的方法.该方法被用于被动声纳目标分类,数值模拟表明了该方法的有效性.
中文关键词: 信息融合  证据组合  分类  目标识别  声纳
Abstract:The conditions for designing an individual classifier, which could increase the performance of combined classification system, are obtained in the opinion of information theory in this paper. The information fusion of combined system in conditions of multiple evidences is implemented by using fuzzy integral. This approach is applied in sonar target classification. Simulation results show that it is efficient.
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基金项目:本文研究得到船舶工业科技基金资助. 本文研究得到船舶工业科技基金资助.
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章新华,林良骥,王骥程.目标识别中信息融合的准则和方法.软件学报,1997,8(4):303-307

ZHANG Xinhua,LIN Liangji,WANG Jicheng.CRITERIONS AND APPROACHES OF INFORMATION FUSION IN TARGET RECOGNITION.Journal of Software,1997,8(4):303-307