物种多样性地理分布格局及其成因是生物地理学和宏观生态学研究的核心问题之一。为了解释物种多样性的分布格局,人们提出了多种假说,其中讨论最多的是能量假说。该假说认为,物种多样性的变化受能量控制。根据能量的不同形式及其对物种...物种多样性地理分布格局及其成因是生物地理学和宏观生态学研究的核心问题之一。为了解释物种多样性的分布格局,人们提出了多种假说,其中讨论最多的是能量假说。该假说认为,物种多样性的变化受能量控制。根据能量的不同形式及其对物种多样性的影响机制,能量假说包括以下几种形式:生产力假说(productivity hypothesis)、水分—能量动态假说(water-energy dynamic hypothesis)、环境能量假说(ambientenergy hypothesis)、寒冷忍耐假说(freezing tolerance hypothesis)以及生态学代谢假说(metabolic theory of ecology,MTE)。本文系统介绍了每种能量假说的含义、所使用的能量形式及表征变量,以及对物种多样性的影响机制,并对不同形式的能量假说进行了比较,在此基础上,分析了每种能量假说的优点和缺点以及各自面临的问题。展开更多
It is understood that the forward-backward probability hypothesis density （PHD） smoothing algorithms proposed recently can significantly improve state estimation of targets. However, our analyses in this paper show ...It is understood that the forward-backward probability hypothesis density （PHD） smoothing algorithms proposed recently can significantly improve state estimation of targets. However, our analyses in this paper show that they cannot give a good cardinality （i.e., the number of targets） estimate. This is because backward smoothing ignores the effect of temporary track drop- ping caused by forward filtering and/or anomalous smoothing resulted from deaths of targets. To cope with such a problem, a novel PHD smoothing algorithm, called the variable-lag PHD smoother, in which a detection process used to identify whether the filtered cardinality varies within the smooth lag is added before backward smoothing, is developed here. The analytical results show that the proposed smoother can almost eliminate the influences of temporary track dropping and anomalous smoothing, while both the cardinality and the state estimations can significantly be improved. Simulation results on two multi-target tracking scenarios verify the effectiveness of the proposed smoother.展开更多
文摘物种多样性地理分布格局及其成因是生物地理学和宏观生态学研究的核心问题之一。为了解释物种多样性的分布格局,人们提出了多种假说,其中讨论最多的是能量假说。该假说认为,物种多样性的变化受能量控制。根据能量的不同形式及其对物种多样性的影响机制,能量假说包括以下几种形式:生产力假说(productivity hypothesis)、水分—能量动态假说(water-energy dynamic hypothesis)、环境能量假说(ambientenergy hypothesis)、寒冷忍耐假说(freezing tolerance hypothesis)以及生态学代谢假说(metabolic theory of ecology,MTE)。本文系统介绍了每种能量假说的含义、所使用的能量形式及表征变量,以及对物种多样性的影响机制,并对不同形式的能量假说进行了比较,在此基础上,分析了每种能量假说的优点和缺点以及各自面临的问题。
基金co-supported by the National Natural Science Foundation of China(No.61171127)NSF of China(No.60972024)NSTMP of China(No.2011ZX03003-001-02 and No.2012ZX03001007-003)
文摘It is understood that the forward-backward probability hypothesis density （PHD） smoothing algorithms proposed recently can significantly improve state estimation of targets. However, our analyses in this paper show that they cannot give a good cardinality （i.e., the number of targets） estimate. This is because backward smoothing ignores the effect of temporary track drop- ping caused by forward filtering and/or anomalous smoothing resulted from deaths of targets. To cope with such a problem, a novel PHD smoothing algorithm, called the variable-lag PHD smoother, in which a detection process used to identify whether the filtered cardinality varies within the smooth lag is added before backward smoothing, is developed here. The analytical results show that the proposed smoother can almost eliminate the influences of temporary track dropping and anomalous smoothing, while both the cardinality and the state estimations can significantly be improved. Simulation results on two multi-target tracking scenarios verify the effectiveness of the proposed smoother.
