The paper deals with the particle filter in state estimation of a discrete-time nonlinear non-Gaussian system. The goal of the paper is to design a sample size adaptation technique to guarantee a quality of a filtering estimate produced by the particle filter which is an approximation of the true filtering estimate. The quality is given by a difference between the approximate filtering estimate and the true filtering estimate. The estimate may be a point estimate or a probability density function estimate. The proposed technique adapts the sample size to keep the difference within pre-specified bounds with a pre-specified probability. The particle filter with the proposed sample size adaptation technique is illustrated in a numerical example.
We compared the photosynthetic traits in response to soil water availability in an endangered plant species Mosla hangchowensis Matsuda and in a weed Mosla dianthera (Buch.-Ham.) Maxim. The highest diurnal mean net photosynthetic rate (PNmean), stomatal conductance (gs), and water use efficiency (WUE) of both species occurred at 60 % soil water holding capacity (WHC), while the lowest values occurred at 20 % WHC. The PNmean, gs, and chlorophyll (Chl) a and b contents of M. hangchowensis were lower than those of M. dianthera, while the physiological plasticity indices were higher than those of M. dianthera. M. hangchowensis had strong adaptability to the changing soil water status but weak extending population ability in its habitats because of the low PNmean, which may be one of the causes of its endangerment. and Y. Ge ... [et al.].