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Distributed Kalman Filtering Fusion with Packet Loss or Intermittent Communications from Local Estimators to Fusion Center: This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermitte...; LUO Yingting,ZHU Yunmin Department of Mathematics,Sichuan University,Chengdu,Sichuan 610064,P.R.China.; 文献传递

Optimal State Estimation of Linear Discrete-time Systems with Correlated Random Parameter Matrices: ＜正＞In this paper,dynamic systems with correlated random parameter matrices are considered.Firstly,we consider ...; SHEN Xiaojing~(1,2),ZHU Yunmin~1,LUO Yingting~1 1.Department of Mathematics Sichuan University Chengdu,Sichuan 610064,P.R.China 2.Department of Computer Science Sichuan University Chengdu,Sichuan 610064,P.R.China; 文献传递

Minimizing Euclidian State Estimation Error for Uncertain Dynamic Systems Based on Multisensor and Multi-Algorithm Fusion: In this paper,a dynamic system with model uncertainty and bounded noises is considered.We propose several effi...; SHEN Xiaojing 1,2,ZHU Yunmin1,SONG Enbin1,LUO Yingting1,YOU Zhisheng2 1.Department.of Mathematics,Sichuan University Chengdu,Sichuan 610064,P.R.China2.Department of Computer Science,Sichuan University Chengdu,Sichuan 610064,P.R.China; 文献传递

低复杂度的渐近最优N-P检测: 考虑高斯模型下的多传感器检测问题,按照Neyman-Pearson准则,即在给定虚警概率允许的上界情况下极大化检测概率.众所周知,Neyman-Pearson准则下最优的检测是似然比（LRT）检测.但多传感器系统下的高维...; 王婷婷宋恩彬; 关键词：高斯模型虚警概率矩阵分解

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国家自然科学基金(60901037)