有限样本下煤硫分典型值的自举模拟取样估计

在对无烟煤硫分基础统计学特征分析的基础上，采用内核密度估计对硫分数据多态性进行了研究，根据非正态分布的特点，使用Bootstrap计算机模拟取样方法对试验样本值模拟重复取样，以多次Bootstrap模拟取样的均值与标准误差作为无烟煤硫分有限样本典型值及标准误差的稳健估计，实践证明，Bootstrap模拟取样估计对无烟煤硫分典型值的估计是有效的.     

Bootstrap interval with application in environmental monitoring

ABSTRACT

Environmental research data usually present high variability because of the presence of outlier values. This study sought to apply the interval bootstrap method, as compared to Chebyshev’s Theorem, for the statistical assessment of environmental data with anomalous values. The results obtained showed that: (a) the bootstrap method is an excellent alternative in the assessment of environmental data with outliers; (b) the method percentile bootstrap (Boot-perc-s) presented the lower interval amplitude to the concentrations of ²²⁶Ra, and (c) Chebyshev’s Theorem presented the highest interval amplitude for the concentration of ²²⁶Ra.     

200 MHz带宽基带信号发生器的设计与实现

介绍了基于FPGA的基带信号发生器设计方案,主要叙述了成型滤波以及任意重采样内插比等关键技术。该基带信号发生器不仅实现了标准数字调制格式的基带信号发生,而且通过FPGA内部的并行架构设计,实现了500 MHz的高速数据速率,I/Q带宽达到200 MHz。将其应用于矢量信号发生器中,既实现了PSK、ASK、FSK、MSK、QAM等标准数字调制格式的矢量信号,又实现了400 MHz矢量调制带宽。经过测试,在4 M码元速率的情况下,QPSK和512QAM调制格式的EVM分别达到0.7%和1.0%;400 MHz带宽的矢量调制信号频响小于1 dB。     

A GENERALIZED BLOCK BOOTSTRAP FOR SEASONAL TIME SERIES

When time‐series data contain a periodic/seasonal component, the usual block bootstrap procedures are not directly applicable. We propose a modification of the block bootstrap – the generalized seasonal block bootstrap (GSBB) – and show its asymptotic consistency without undue restrictions on the relative size of the period and block size. Notably, it is exactly such restrictions that limit the applicability of other proposals of block bootstrap methods for time series with periodicities. The finite‐sample performance of the GSBB is also illustrated by means of a small simulation experiment.     

Medical Image Retrieval Based on Multi-Layer Resampling Template

Medical image application in clinical diagnosis and treatment is becoming more and more widely, How to use a large number of images in the image management system and it is a very important issue how to assist doctors to analyze and diagnose. This paper studies the medical image retrieval based on multi-layer resampling template under the thought of the wavelet decomposition, the image retrieval method consists of two retrieval process which is coarse and fine retrieval. Coarse retrieval process is the medical image retrieval process based on the image contour features. Fine retrieval process is the medical image retrieval process based on multi-layer resampling template, a multi-layer sampling operator is employed to extract image resampling images each layer, then these resampling images are retrieved step by step to finish the process from coarse to fine retrieval.     

基于数据场的概率神经网络算法

提出基于数据场高斯势约简概率神经网络结构,基本思路:引入数据场估计训练集各类概率密度,选择局部极大密度估计样本构造网络;对初始网络迭代训练,依次扩展各类具有最大密度估计值的误分样本至模式层并调整权重参数,直至满足指定精度.采用增量密度计算,保证快速迭代和高概率收敛.基于重采样技术进一步提升泛化精度.实验表明,提出的算法...     

包络变形对阶比分析结果的影响及消除方法

转速变化的滚动轴承故障诊断通常先采用计算阶比跟踪技术消除变转速的影响,再进行阶比分析获得故障特征。然而,等角度重采样会引起冲击包络变形进而导致阶比分析结果产生偏差,在转速变化范围较大时这个偏差必须要受到重视。本文的主要工作是介绍了等角度重采样方法,仿真了包络变形对阶比分析结果的影响,给出了峰值点间隔变化量详细的理论推导,提出了通过修正角度变换值来消除包络变形影响的方法,并进行了实验验证。研究结果显示,包络在宽窄方向的变形对阶比分析结果没有影响;相邻包络峰值点间隔的变化对阶比分析结果产生影响;在角度序列逐点减去峰值点间隔变化量可消除包络变形对阶比分析结果的影响。     

智能变电站重采样应用研究及其线性插值法误差分析

针对重采样环节在智能变电站应用过程中所引入的误差,分析了其在智能变电站中的具体应用场景,得到采样同步和采样频率转换两种典型方法。以线性插值算法为研究对象,通过建立矢量模型分析并结合实验验证的方法,得到线性插值幅频特性。结果表明,信号频率与插值位置是直接影响重采样精度的两个主要原因,线性插值误差对保护专业的影响可以忽略,但是对测量与计量专业的影响较大。通过提高采样率,改进同步或插值算法等办法,重采样误差可以减少甚至消除。     

Block bootstrap methods for the estimation of the intensity of a spatial point process with confidence bounds

This paper deals with the estimation of the intensity of a planar point process on the basis of a single point pattern, observed in a rectangular window. If the model assumptions of stationarity and isotropy hold, the method of block bootstrapping can be used to estimate the intensity of the process with confidence bounds. The results of two variants of block bootstrapping are compared with a parametric approximation based on the assumption of a Gaussian distribution of the numbers of points in deterministic subwindows of the original pattern. The studies were performed on patterns obtained by simulation of well‐known point process models (Poisson process, two Matérn cluster processes, Matérn hardcore process, Strauss hardcore process). They were also performed on real histopathological data (point patterns of capillary profiles of 12 cases of prostatic cancer). The methods are presented as worked examples on two cases, where we illustrate their use as a check on stationarity (homogeneity) of a point process with respect to different fields of vision. The paper concludes with various methodological discussions and suggests possible extensions of the block bootstrap approach to other fields of spatial statistics.     

采样技术在武器试验中的应用

根据武器试验的具体特点，提出采用重采样技术解决对试验测试系统的过高要求，并压缩数据量便于存储．某型多管火箭炮实测数据的处理结果与理论计算对比表明，该方法所得结果可信，可用于武器试验测试中．