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兰州理工大学 [8]

西安交通大学 [2]

清华大学 [1]

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	An improved UPF object tracking algorithm based on multi-feature fusion 期刊论文 Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 2014, 卷号: 48, 期号: 10, 页码: 1473-1478 作者: Li, Xiao-Xu; Dai, Bin; Cao, Jie 收藏 \| 浏览/下载：32/0 \| 提交时间：2020/11/14 Image processing Kalman filters Textures Uncertainty analysis Iterated Kalman filter Multiple features fusions Object Tracking Uncertainty measurements Unscented particle filters
	Improved UPF algorithm based on Gaussian Sigma points selection 期刊论文 Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2014, 卷号: 44, 期号: 5, 页码: 1435-1440 作者: Cao, Jie; Dai, Bin; Li, Xiao-Xu 收藏 \| 浏览/下载：29/0 \| 提交时间：2020/11/14 Approximation algorithms Computer applications Distribution functions Gaussian distribution Monte Carlo methods Metropolis Hastings Particle filter Particle filter algorithms Posterior probability Proposal distribution Sigma point Unscented Kalman Filter Unscented particle filters
	Adaptive unscented particle filter algorithm under unknown noise 期刊论文 Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2013, 卷号: 43, 期号: 4, 页码: 1139-1145 作者: Li, Yu-Chen; Li, Zhan-Ming 收藏 \| 浏览/下载：26/0 \| 提交时间：2020/11/14 Adaptive filters Clutter (information theory) Data processing Distribution functions Information filtering Kalman filters Monte Carlo methods Target tracking Anti-noise ability Estimation errors Particle filter Proposal distribution Statistic characteristics Unknown noise Unscented Kalman Filter Unscented particle filters
	Video target tracking algorithm based on multi-feature adaptive fusion 期刊论文 Journal of Computational Information Systems, 2013, 卷号: 9, 期号: 11, 页码: 4617-4628 作者: Wang, Jinhua; Cao, Jie; Li, Wei; Li, Jun 收藏 \| 浏览/下载：14/0 \| 提交时间：2020/11/14 Linear regression Monte Carlo methods Target tracking Adaptive fusion Feature fusion Object Tracking Observation information Particle filter Statistical linear regressions Unscented particle filters Unscented transformations
	Speaker tracking based on audio-visual fusion with unknown noise 会议论文 Yangzhou, Jiangsu, China, August 23, 2013 - August 25, 2013 作者: Cao, Jie; Li, Jun; Li, Wei 收藏 \| 浏览/下载：5/0 \| 提交时间：2020/11/15 Acoustic noise Audio acoustics Distribution functions Kalman filters Monte Carlo methods Tracking (position) Audio-visual fusion Noise statistics Optimal distribution functions Particle filter Particle filter algorithms Speaker tracking Statistic characteristics Unscented Kalman Filter
	Multi-features fusion tracking method under unknown noise 期刊论文 Information Technology Journal, 2013, 卷号: 12, 期号: 4, 页码: 614-622 作者: Feng, Xin; Wang, Xiaoming; Dang, Jianwu; Shen, Yu 收藏 \| 浏览/下载：18/0 \| 提交时间：2020/11/14 Adaptive filtering Adaptive filters Clutter (information theory) Distribution functions Kalman filters Monte Carlo methods State estimation D S evidence theory Multi-features fusions Optimal distribution functions Particle filter Statistic characteristics Statistical characteristics Unscented Kalman Filter Video targets
	Object tracking algorithm based on adaptive unscented particle filter 期刊论文 Guangdianzi Jiguang/Journal of Optoelectronics Laser, 2012, 卷号: 23, 期号: 10, 页码: 1983-1989 作者: Li, Yu-Chen; Li, Zhan-Ming 收藏 \| 浏览/下载：15/0 \| 提交时间：2020/11/14 Adaptive filters Algorithms Estimation Monte Carlo methods Nonlinear filtering Anti-noise ability Complex scenes Estimation errors High precision Object Tracking Object tracking algorithm Optimal distribution functions Particle filter Sage-husa Statistic characteristics Unknown noise Unscented Kalman Filter Unscented particle filters
	Cubature particle filter and its application 期刊论文 Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University, 2011, 卷号: 45, 期号: [db:dc_citation_issue], 页码: 13-17 作者: Mu, Jing; Cai, Yuanli; Zhang, Junmin 收藏 \| 浏览/下载：2/0 \| 提交时间：2019/12/10 Cubature particle filters Cubature rules Discrete - time systems Extended particle filters Generic particle filters Numerical integration methods Particle filter Unscented particle filters
	State tracking measurement method using particle filter based on radial basis function neural network 期刊论文 2010, 2010 Wang Xue; Wang Sheng; Ma Junjie 收藏 \| 浏览/下载：4/0
	Unscented particle filtering with Particle Swarm Optimization for estimating nonlinear system 会议论文作者: Li, Ming; L., Yuan; W., Du 收藏 \| 浏览/下载：1/0 \| 提交时间：2020/11/15 Monte Carlo methods Nonlinear systems Computation complexity Estimation precision Objective functions Optimization approach Particle degeneracy Particle Filtering Particle swarm Unscented particle filters

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