Analysis of particle methods for structured population models with nonlocal boundary term in the framework of bounded Lipschitz distance

Recently developed theoretical framework for analysis of structured population dynamics in the spaces of nonnegative Radon measures with a suitable metric provides a rigorous tool to study numerical schemes based on particle methods. The approach is based on the idea of tracing growth and transport of measures which approximate the solution of original partial differential equation. In this article, we present analytical and numerical study of two versions of Escalator Boxcar Train algorithm which has been widely applied in theoretical biology, and compare it to the recently developed split‐up algorithm. The novelty of this article is in showing well‐posedness and convergence rates of the schemes using the concept of semiflows on metric spaces. Theoretical results are validated by numerical simulations of test cases, in which distances between simulated and exact solutions are computed using flat metric. © 2014 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 30: 1797–1820, 2014     

A spectral transfer procedure for application of a single class-model to spectra recorded by different near-infrared spectrometers for authentication of olives in brine

Analytical methods for confirmation of food authenticity claims should be rapid, economic, non-destructive and should not require highly skilled personnel for their deployment. All such conditions are satisfied by spectroscopic techniques. In order to be extensively implemented in routine controls, an ideal method should also give a response independent of the particular equipment used. In the present study, near-infrared (NIR) spectroscopy was used for verifying authenticity of commercial olives in brine of cultivar Taggiasca. Samples were analysed in two laboratories with different NIR spectrometers and a mathematical spectral transfer correction – the boxcar signal transfer (BST) – was developed, allowing to minimise the systematic differences existing between signals recorded with the two instruments. Class models for the verification of olive authenticity were built by the unequal dispersed classes (UNEQ) method, after data compression by disjoint principal component analysis (PCA). Models were validated on an external test set.     

以YAG／DYE激光器为光源的脉冲喇曼光谱测试系统研究

本文介绍了以ＹＡＧ／ＤＹＥ激光器为光源，双光栅单色仪，Ｂｏｘｃａｒ积发平均器和ｘ－ｙ记录仪作为信息处理，放大和记录装置组成的脉冲喇曼光谱实验系统及使用该系统所作的液体、固体脉冲喇曼斯托克斯、反斯托克斯和相干反斯托克斯（ＣＡＲＳ）光谱。并讨论了脉冲喇曼光谱与连续喇曼光谱的优缺点及系统所存在的一些问题。     

Study of the interdependency of the data sampling ratio with retention time alignment and principal component analysis for gas chromatography

An in-depth study is presented to better understand how data reduction via averaging impacts retention alignment and the subsequent chemometric analysis of data obtained using gas chromatography (GC). We specifically study the use of signal averaging to reduce GC data, retention time alignment to correct run-to-run retention shifting, and principal component analysis (PCA) to classify chromatographic separations of diesel samples by sample class. Diesel samples were selected because they provide sufficient complexity to study the impact of data reduction on the data analysis strategies. The data reduction process reduces the data sampling ratio, S(R), which is defined as the number of data points across a given chromatographic peak width (i.e., the four standard deviation peak width). Ultimately, sufficient data reduction causes the chromatographic resolution to decrease, however with minimal loss of chemical information via the PCA. Using PCA, the degree of class separation (DCS) is used as a quantitative metric. Three "Paths" of analysis (denoted A-C) are compared to each other in the context of a "benchmark" method to study the impact of the data sampling ratio on preserving chemical information, which is defined by the DCS quantitative metric. The benchmark method is simply aligning data and applying PCA, without data reduction. Path A applies data alignment to collected data, then data reduction, and finally PCA. Path B applies data reduction to collected data, and then data alignment, and finally PCA. The optimized path, namely Path C, is created from Paths A and B, whereby collected data are initially reduced to fewer data points (smaller S(R)), then aligned, and then further reduced to even fewer points and finally analyzed with PCA to provide the DCS metric. Overall, following Path C, one can successfully and efficiently classify chromatographic data by reducing to a S(R) of ～15 before alignment, and then reducing down to S(R) of ～2 before performing PCA. Indeed, following Path C, results from an average of 15 different column length-with-temperature ramp rate combinations spanning a broad range of separation conditions resulted in only a ～15% loss in classification capability (via PCA) when the loss in chromatographic resolution was ～36%.     

基于Boxcar滤波器的荧光检测二氧化硫信号的去噪研究

荧光法以物质发射的荧光强度与浓度之间的线性关系进行定量分析。当采用荧光法检测大气中的二氧化硫等有害气体时,由于光电探测器等光电元件在无荧光时,仍会产生暗电流噪声,使得本底噪声信号对测量结果有直接的影响。在分析Boxcar滤波算法的基础上,运用小波滤波、EMD滤波和Boxcar滤波三种算法对淹没在本底噪声中的荧光信号进行有效提取和恢复,较之前两种滤波方法,Boxcar滤波效果更佳,对本底噪声的抑制更强,并验证了取样次数影响着荧光信号的信噪比。     

飞秒时间分辨取样光谱仪的研制

研制的飞秒（１０＾１５ｓ）时间分辨取样光谱仪由三部分组成；（１）飞秒激光探针弥散补偿光学系统，（２）氩激光泵浦参钛兰宝石飞秒激光系统，（３）信号探测，数据采集分析处理掺钛兰宝石飞秒激光器在７Ｗ氩激光全线泵浦下，能输出平均功率４００ｍＷ、持续期５０ｆｓ到５００ｆｓ的脉冲，其光谱可在７５０ｎｍ到９２０ｎｍ范围内调经ＬＢＯ晶体倍频，能得到３７５ｎｍ到４６０ｎｍ的二次谐波，整体取样光谱仪的时间分辨为９０ｆ     

基于ROEWA和Gabor滤波的SAR图像边缘提取

针对合成孔径雷达(SAR)图像特有的乘性噪声和非恒虚警统计特性很难正确提取目标边缘的问题,提出了在指数加权均值比(ROEWA)算子基础上寻找自适应的最佳局域Gabor滤波器进行目标边缘提取的方法。利用Gabor滤波器具有的多方向特性确定边缘方向,然后用最大似然估计纠正错误边缘方向,重新结合视觉细胞倍频程计算出Gabor函数的最佳局域滤波参数,提取出SAR图像的正确边缘。实验表明,该方法取得很好边缘提取效果,并且后期分割出的目标更符合实际目标形态,具有较强的通用性。     

Boxcar积分器模型参数选择

利用计算机运算速度快、描述形象的特点设计一模型参数选择软件,可根据被恢复波形的要求灵活地选择、计算或修正参数值,给 Ｂｏｘｃａｒ 的使用带来了很大的方便     

红外物质水份测量仪及其信号处理方法

首次在红外水份测量仪中采用数字Ｂｏｘｃａｒ滤波器这一现代数字滤波技术，从而大大提高了该仪器的测量精度。对Ｂｏｘｃａｒ滤波算法进行了严格的理论推导，并给出了计算机实现方法。