Recursive generalized extended least squares and RML algorithms for identification of bilinear systems with ARMA noise

Bilinear systems are considered as a particular class of nonlinear systems including the state variables which are typically used for online identification. By using a recursive identification method and the maximum likelihood principle, this paper presents two recursive-based algorithms to identify the parameters of bilinear in parameter systems with ARMA noise. In this regard, recursive generalized extended least squares (RGELS) and recursive Maximum Likelihood (RML) algorithms have been proposed for identification of bilinear systems. These algorithms can be used as an alternative choice in system identification with acceptable performance. The proposed algorithms estimate the correlated noise parameters with high accuracy by making full use of the measurement data. Simulation results indicate that the proposed algorithms are effective for online identification of bilinear in parameter systems with high convergence speed.     

Improvement of quantitative analysis of molybdenum element using PLS-based approaches for laser-induced breakdown spectroscopy in various pressure environments

An experimental setup has been designed and realized in order to optimize the characteristics of laser-induced breakdown spectroscopy system working in various pressure environments. An approach combined the normalization methods with the partial least squares(PLS) method are developed for quantitative analysis of molybdenum(Mo) element in the multi-component alloy,which is the first wall material in the Experimental Advanced Superconducting Tokamak. In this study, the different spectral normalization methods(total spectral area normalization,background normalization, and reference line normalization) are investigated for reducing the uncertainty and improving the accuracy of spectral measurement. The results indicates that the approach of PLS based on inter-element interference is significantly better than the conventional PLS methods as well as the univariate linear methods in the various pressure for molybdenum element analysis.     

盘县火腿自然发酵过程中理化和风味特征

分析盘县火腿自然发酵过程中理化特性和风味特征的变化，并结合香气活度值（odor activity value，OAV）和偏最小二乘回归（partial least squares regression，PLSR）分析确定盘县火腿主体香气成分。结果表明：盘县火腿理化特性在发酵过程中发生显著变化（P＜0.05），pH值和NaCl含量显著上升，而水分活度、水分含量和肌内脂肪含量显著下降，亮度值和黄度值呈持续下降趋势，而红度值先降低后升高；随着发酵的进行，盘县火腿中风味物质的种类从25 种增加至40 种，含量从（218.50±22.14） μg/kg上升至（1 044.49±51.47） μg/kg，其中醛类物质的种类和含量最丰富；OAV分析筛选出16 种主体香气物质，PLSR模型显示3-甲基丁醛、十二醛、十六醛、(Z)-9-十八烯醛和十八醛对盘县火腿肉香、清香和油脂香有显著贡献。     

近红外光谱法对松原不同品种大米的确证探究

该文提出一种对松原不同品种大米进行判别的方法,对来自松原的稻花香、小高粱、通系926、吉粳515、农大521,5个品种共368个大米样品,利用波数范围为12000 cm^-1~4000 cm^-1的傅里叶近红外光谱仪获取光谱数据并对数据进行6种方法的预处理。结果表明,一阶导数结合SG9点平滑为最佳预处理方法,并用偏最小二乘判别(partial least squares discrimination analysis,PLS-DA)方法对校正样本建立判别分析模型,用验证集对模型进行验证,模型对验证集中稻花香、小高粱、通系926、吉粳515、农大521共5个品种的识别率均为100%;且优于主成分分析的结果。用来自柳河和梅河的稻花香样本与松原的稻花香样本进行产地判别,结果显示,此模型可以将松原样本与非松原样本进行判别。     

不同烹饪方式对干腌火腿理化、感官及风味品质的影响

熟肉制品的理化、感官和风味品质与烹饪方式密切相关，通过比较高压、微波、蒸制和煮制4 种烹饪方式对盘县火腿理化和营养特性、风味品质及感官评价的影响，筛选出最适宜盘县火腿的烹饪方法。结果表明：蒸制和煮制火腿色泽更好，pH值较高，分别为6.10和8.16，水分含量较高，分别为35.70%和35.20%，盐含量和烹饪损失率更低，分别为28.01%、5.15%和28.06%、4.99%；微波处理火腿粗脂肪和粗蛋白含量最高，分别为6.48%和55.14%；4 种烹饪方式均导致火腿中风味物质种类减少，但微波、蒸制和煮制可增加风味物质含量，特别是蒸制；聚类分析和Biplot分析同样显示出蒸制对原料火腿风味的改善作用；主成分分析结果表明，15 种特征香气成分中有7 种与蒸制火腿相关，包括2-甲基丁醛、3-甲基丁醛、己醛、壬醛、庚醛、辛醛和(E)-2-癸烯醛；感官评价结果表明，蒸制火腿的肉香属性得分最高，偏最小二乘回归相关性分析显示，这可能与其高含量的3-甲基丁醛、己醛和壬醛有关。盘县火腿最佳烹饪方式为蒸制，有助于改善其理化特性和风味品质。     

基于中红外光谱技术的甘氨酸铁螯合物判别研究

目的研究基于中红外光谱(mid infrared spectroscopy,MIRS)技术定性判别有机微量元素添加剂掺假的可行性。方法以甘氨酸铁螯合物和硫酸亚铁为研究对象,分析样品的中红外光谱,解析不同样品光谱的特异性;建立偏最小二乘判别(partial least squares discriminant analysis,PLS-DA)校正模型对掺假样品进行判别,并比较不同预处理方法、全光谱与特征波段对校正模型判别效果的影响。结果甘氨酸铁螯合物与硫酸亚铁光谱差异显著,主要分布在(3500～3000) cm~(-1)、(1600～1300) cm~(-1)、(1300～1000) cm~(-1)、(660～550) cm~(-1),通过采用平滑(smoothing,SM)、归一化(normalization,Norm)与一阶导数(first derivative,FD)相结合的方法对光谱进行预处理,结合1300 cm~(-1)～1000 cm~(-1)波段建立的PLS-DA校正模型判别效果最优,校正集的判别正确率为97.5%,验证集的判别正确率为100.0%,对外部样品的判别正确率达到92.7%。结论中红外光谱技术结合化学计量学方法能够对甘氨酸铁螯合物的掺假进行准确判别。     

基于最小包容区域的球度误差评定方法

针对球度误差评定方法存在原理误差或模型误差,提出了一种符合最小包容区域定义的球度误差评定方法,即将几何搜索逼近算法与基于最小包容区域法的球度误差评定的几何结构和定义结合起来的准确评定方法。对仿真数据和其他文献中的数据进行了评定。所提方法与其他方法的评定结果表明,所提方法可以准确地找到最小包容区域球的球心并给出球度误差的精确解。     

基于TLS的非线性GM-AR高边坡变形预测模型及应用

为提高传统GM-AR模型预测精度,提出一种基于整体最小二乘(TLS)的非线性GM-AR变形预测模型。首先利用TLS参数估计的GM(1,1)模型提取变形序列中具有确定性的趋势项,然后再对剔除趋势项后的随机部分建立TLS参数估计的AR预测模型,最后叠加两者的预测结果作为最终的变形预测结果,并以三峡库区某高边坡的变形数据为例对模型进行验证。结果表明,相对于传统最小二乘(LS)参数估计的非线性GM-AR模型及GM(1,1)、AR两个单一模型,基于TLS的非线性GM-AR模型的预测精度更高,可在变形预测中应用。     

LTAG加氢单元原料和产品烃类组成中红外光谱快速分析技术

LTAG工艺在工况调整过程中需要对加氢单元LCO加氢原料和产物烃类组成的进行监控，本研究采集大量催化和加氢柴油样品的中红外光谱结合偏最小二乘方法建立LCO加氢原料和产物烃类组成的中红外分析模型。利用该方法可快速得到LCO加氢原料和产物的详细烃类组成，分析结果和质谱方法分析结果具有良好的一致性，与近红外光谱快速分析方法相比较具有更高的准确性。该方法操作简单、重复性好，能满足现场快速分析的需求。     

Using a spectral scaling structured BFGS method for constrained nonlinear least squares

In this paper, we use a spectral scaled structured BFGS formula for approximating projected Hessian matrices in an exact penalty approach for solving constrained nonlinear least-squares problems. We show this spectral scaling formula has a good self-correcting property. The reported numerical results show that the use of the spectral scaling structured BFGS method outperforms the standard structured BFGS method.