SMC框架中引入残差信息的分层重采样策略.pdfVIP

30 2010 ，46 （21 ） Computer Engineering and Applications 计算机工程与应用 SMC 框架中引入残差信息的分层重采样策略 1，2 2 2 吴 刚 ，唐振民 ，杨静宇 1，2 2 2 WU Gang ，TANG Zhen-min ，YANG Jing-yu 1.南京工程学院 车辆工程系，南京 211167 2.南京理工大学 计算机科学与技术学院，南京 210094 1.Department of Vehicle Engineering ，Nanjing Institute of Technology ，Nanjing 211167 ，China 2.School of Computer Science Technology ，Nanjing University of Science and Technology ，Nanjing 210094 ，China E-mail ：zdhxwg@ WU Gang ，TANG Zhen-min ，YANG Jing-yu.Stratified resampling strategy imported by residual information in SMC framework.Computer Engineering and Applications ，2010 ，46 （21 ）：30-33. Abstract ：Recently ，sequential Monte Carlo theory has been applied abroad in different domains such as self-determined navi- gation ，non-linear estimation and finance ，and it attracts researchers more and more.A stratified resampling strategy is brought forward imported by residual information in this work.Accumulative distributing function is constructed by importing residu- als of particles ’weights.Synchronously ，sequential stochastic numbers are gradually produced by arranging on stochastic mus- ter.The way improves the rationality and efficiency of sampling strategy.The method is confirmed by experiment based on emulational program.Compared with residual resampling strategy ，polynomial resampling strategy and genetic resampling strate- gy ，the systemic errors about resampling strategy are lowest in posterior mean error ，mean square error and running time.The improved resampling strategy is embedded in object tracking algorithm.The correlative results show astringency and anti- noise-capability about sampling strategy are excellent on data based on standard testing video. Key words ：sequential Monte Carlo ；resampling ；stratified ；residual 摘 要：近年来序列蒙特卡罗理论及其应