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	A New Algorithm for Navigation Trajectory Prediction of Land Vehicles Based on a Generalised Extended Extrapolation Model 期刊论文 OAI收割 JOURNAL OF NAVIGATION, 2019, 卷号: 72, 期号: 5, 页码: 1217-1232 作者: Shang, Junna; Liu, Can; Shi, Huli; Cheng, Tao; Yue, Keqiang \| 收藏 \| 浏览/下载：35/0 \| 提交时间：2020/03/10 Location prediction Generalised extended prediction algorithm Previous data Track extrapolation
	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：74/0 \| 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).
	Implementation of a fast simulation algorithm for terrain based on dynamic LOD (EI CONFERENCE) 会议论文 OAI收割 IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011, August 16, 2011 - August 18, 2011, Chengdu, China 作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：40/0 \| 提交时间：2013/03/25 In-depth study and explore dynamic quad tree rendering of large-scale terrain. Investigated the problems which was urgently to be solved about quad tree. Studied the features and application of dynamic quad tree algorithm and static quad tree algorithm. Analyze and explore the problems about quad tree construction data storage that is significant in modeling removing of the grid back and elimination of T-type fracture. In this study an algorithm based on storage array was proposed on the basis of the previous research to eliminate T-type fracture. The results showed that the new algorithm not only enhance the streamline effect but also increased the rendering speed in the large-scale virtual terrain rendering process. The draw rate was enhanced from 8-10 frames/s up to 20-23 frames/s. 2011 IEEE.
	SoC test data compression technique based on RLE-G (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Advanced Measurement and Test, AMT 2010, May 15, 2010 - May 16, 2010, Sanya, China 作者: Liu W.; Yang L.; Yang L.; Zheng X. 收藏 \| 浏览/下载：60/0 \| 提交时间：2013/03/25 Test data compression has been an effective way to reduce test data volume and test time as well as to solve automatic test equipment (ATE) memory and bandwidth limitation. We analyze the limitations of current test data compression algorithm and draw on the previous experience to deduce an optimal compression coding model suitable for SoC test data. In addition in this paper we make full use of the relevance of the test vectors and the advantages of statistical coding to present an efficient test data compression method RLE-G based on the coding model and give the RLE-G the optimal compression efficiency of the boundary conditions and realization steps. The experimental results for ISCAS 89 benchmark circuits demonstrate RLE-G have the excellent advantages of high compression ratio. (2010) Trans Tech Publications.
	A novel spatial clustering algorithm based on Delaunay triangulation 会议论文 OAI收割 International Conference on Earth Observation Data Processing and Analysis, ICEODPA,, Wuhan, China, December 28, 2008 - December 30,2008 Yang, Xiankun; Cui, Weihong 收藏 \| 浏览/下载：35/0 \| 提交时间：2014/12/07 Exploratory data analysis is increasingly more necessary as larger spatial data is managed in electro-magnetic media. Spatial clustering is one of the very important spatial data mining techniques. So far a lot of spatial clustering algorithms have been proposed. In this paper we propose a robust spatial clustering algorithm named SCABDT (Spatial Clustering Algorithm Based on Delaunay Triangulation). SCABDT demonstrates important advantages over the previous works. First it discovers even arbitrary shape of cluster distribution. Second in order to execute SCABDT we do not need to know any priori nature of distribution. Third like DBSCAN Experiments show that SCABDT does not require so much CPU processing time. Finally it handles efficiently outliers. 2008 SPIE.