基于Pearson系统模型的盲信号分离研究

独立分量分析是盲源分离的主流技术。自然梯度算法是其中非常重要的算法之一。介绍一种最大似然框架下的Pear-son系统模型。该方法的优点是无须知晓信号的概率分布,实验结果表明,该算法能有效地分离随机混合的信号,特别对于非对称源有比同类算法更理想的效果。

Statistical analysis of fracture properties based on particle swarm optimization and Pearson correlation coefficient method

Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.

基于改进降维法的可靠度分析

单变量维数缩减法可以高效、准确地进行结构响应矩的分析。与传统的一阶可靠度算法FORM(First Order Reliability Method),二阶可靠度算法SORM(Second Order Reliability Method)相比,该方法不需要响应的导数,也不需要迭代搜索最可能失效点。然而近期的研究发现,该方法中基于矩的积分方法MBQR(Moment Based Quadrature Rule)在积分点增加之后求解线性方程组时,会出现系数矩阵的奇异性并导致数值结果不稳定,从而影响了该方法的效率和精度。提出了归一化的基于矩的积分方法,有效地解决了数值求解过程中的不稳定问题。利用降维法求解结构响应统计矩,并通过Pearson系统计算响应的概率密度函数,从而获得失效概率。算例表明了本文方法的计算效率和精度。

The Development of a Geographic Information System(GIS) Database for Jiuzhaigou National Nature Reserve and Its Application

The objective of this paper is to develop a GIS(Geographic Information System) database for Jiuzhaigou National Nature Reserve(Jiuzhaigou,hereafter) in China and demonstrate its application as a research tool.A cost-effective procedure was developed to compile a variety of geographical and biological data of the study area in terms of popular GIS format such as shape files.These files were further calibrated and validated using field surveys data.The developed GIS database was used to quantify the distributions of the wildlife(amphibians,mammals,and birds) using the distances of the wildlife to the centerline of the bus-tour routes.The Pearson correlation coefficient was used to quantify the correlation in space between pairs of different wildlife using the number of habitats for given space contexts.An ArcObject-based macro was developed to perform the analysis.The results showed the majority of the habitats of wildlife are located in the proximity of the tour-bus routes with an average distance ranging from 564 to 894 m depending on types of wildlife.This indicates a possibility of the disturbance to the wildlife by human activities.The correlation coefficient of the wildlife ranged from 0.36 to 0.64 depending on pairs of wildlife,indicating some correlations in space.However,due to the limited sample size,the statistical significances need to be further investigated.This paper has successfully demonstrated the use of the GIS-based database as a research tool for environmental study.