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	A Gaussian mixture regression model based adaptive filter for non-Gaussian noise without a priori statistic 期刊论文 OAI收割 SIGNAL PROCESSING, 2022, 卷号: 190, 页码: 13 作者: Cui, Haoran; Wang, Xiaoxu; Gao, Shuaihe; Li, Tiancheng \| 收藏 \| 浏览/下载：33/0 \| 提交时间：2021/11/26 Nonlinear adaptive filter Unknown and non-Gaussian noises Variational Bayesian Gaussian mixture model
	Improved Adaptive Hybrid Compensation for Compound Faults of Non-Gaussian Stochastic Systems 期刊论文 OAI收割 IEEE ACCESS, 2019, 卷号: 7, 页码: 51284-51294 作者: Hu, Kaiyu; Wen, Changyun; Yusup, Aili \| 收藏 \| 浏览/下载：25/0 \| 提交时间：2020/03/10 Non-Gaussian stochastic systems nonlinear dynamical systems compound faults adaptive estimation fault-tolerant control robust stability
	基于高斯和粒子滤波的地形辅助导航方法研究学位论文 OAI收割工学硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2011 廖威收藏 \| 浏览/下载：57/0 \| 提交时间：2015/09/02 地形辅助导航数字高程模型非线性非高斯模型高斯和粒子滤波混合高斯模型 Terrain aided navigation Digital elevation model Nonlinear non-Gaussian system model Gaussian sum particle filter Gaussian mixture model
	The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: Sun H.; Han H.-X.; Sun H. 收藏 \| 浏览/下载：59/0 \| 提交时间：2013/03/25 Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
	Study on image real-time interpretation based on particle filter (EI CONFERENCE) 会议论文 OAI收割 2011 International Conference on Mechatronic Science, Electric Engineering and Computer, MEC 2011, August 19, 2011 - August 22, 2011, Jilin, China 作者: Liu S.-J. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 In order to satisfy to the real-time requirement of image interpretation system in photoelectric measurement equipments a kind of hardware acceleration system with MIMD distributed multi-processor architecture based on SOPC technology is designed. The particle filter algorithm is proposed to process image interpretation for state estimation problem of nonlinear and non-Gaussian system. This algorithm does not involve conventional linearization transform and has approximated the posterior probability density by a set of discrete particles. Therefore the approximate optimum result is educed. It has a high accuracy and a rapid convergence. Experimental results show that the algorithm be adequate to real time accuracy and robustness meets the requirement of image interpretation and possesses practical significance for engineering applications. 2011 IEEE.
	An evaluation of the nonlinear/non-Gaussian filters for the sequential data assimilation 期刊论文 iSwitch采集 REMOTE SENSING OF ENVIRONMENT, 2008, 卷号: 112, 期号: 4, 页码: 1434-1449 作者: Han, Xujun; Li, Xin 收藏 \| 浏览/下载：34/0 \| 提交时间：2019/10/08 Bayesian filtering nonlinear/non-Gaussian sequential data assimilation Kalman filter particle filter Lorenz model Monte Carlo methods land surface model microwave remote sensing
	非线性系统和非高斯随机系统的故障诊断和容错控制学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2006 作者: 姚利娜收藏 \| 浏览/下载：60/0 \| 提交时间：2015/09/02 故障诊断容错控制非线性时滞系统非高斯随机分布系统奇异系统协作系统 Fault diagnosis Fault tolerant Nonlinear time-delayed systems Non-Gaussian stochastic Singular systems Collaborative systems
	Minimum entropy filtering for multivariate stochastic systems with non-Gaussian noises 期刊论文 OAI收割 IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2006, 卷号: 51, 期号: 4, 页码: 695-700 作者: Guo, L; Wang, H 收藏 \| 浏览/下载：22/0 \| 提交时间：2015/11/07 entropy optimization hybrid probability non-Gaussian systems nonlinear systems stochastic filtering
	Minimum entropy control of closed-loop tracking errors for dynamic stochastic systems 期刊论文 OAI收割 IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2003, 卷号: 48, 期号: 1, 页码: 118-122 作者: Yue, H; Wang, H 收藏 \| 浏览/下载：18/0 \| 提交时间：2015/11/08 entropy non-Gaussian nonlinear optimization stochastic