STABLE DOUBLE LR ALGORITHM AND ITS ERROR ANALYSIS

In this paper, the normative matrices and their double LR transformation with origin shifts are defined, and the essential relationship between the double LR transformation of a normative matrix and the QR transformation of the related symmetric tridiagonal matrix is proved. We obtain a stable double LR algorithm for double LR transformation of normative matrices and give the error analysis of our algorithm. The operation number of the stable double LR algorithm for normative matrices is only four sevenths of the rational QR algorithm for reed symmetric tridiagonal matrices.     

论中国海洋砂矿床类型

本文总结了作者二十多年砂矿工作的经验,搜集了国内近三百处海洋砂矿床(点)五十余种矿床类型划分的资料,比照国外同类型矿床,结合我国矿床特征,提出了新的海洋砂矿分类原则,矿床工业类型、成因-形态类型、成矿时代类型和保存类型等的划分系统,以及今后的找矿方向。     

物理解题中隐含条件的挖掘——以2019年高考全国Ⅰ卷、Ⅱ卷、Ⅲ卷选择题为例

隐含条件的挖掘和准确把握,在很多时候对于物理问题的快速解决起着关键性的作用,在审题过程中能快速找出隐含条件,并利用隐含条件解题更是在考试过程中准确高效解题的最好方法.本文以2019年高考全国Ⅰ卷、Ⅱ卷、Ⅲ卷选择题为例详细分类探讨了物理解题中隐含条件的挖掘这一问题,希望对于学生如何在题目中快速找出隐含条件有所帮助.     

基于改进型相关向量机的高光谱图像分类

相关向量机(RVM)高光谱图像分类算法是一种基于贝叶斯概率模型的监督机器学习算法,其分类精度较高、测试时间较短。然而算法本身存在训练时间随着训练样本增加直线上升、分类效率整体降低等问题。针对这种情况,提出一种基于改进型相关向量机(VRVM)的高光谱图像分类算法。本算法在传统概率模型中引入一个新的分布,使得计算复杂度较高的积分运算可近似地拆分成两个较为简单的对数和形式。实验结果表明,VRVM高光谱图像分类算法的总体分类精度和相关向量的数量与RVM基本相同,但训练时间随样本数的增加有明显的减少。     

Visual perception of textiles using surface and display samples

In this study, 15 parameters representing textile properties are evaluated by the psychophysical method of categorical judgment with samples presented either in a light booth or on a display to investigate human visual perception based on the textural features of textiles. Visual perceptions of textiles can be expressed by the properties of regularity, smoothness, and warmth, which respectively explain the geometric placement rules of primitive elements, depth information, and emotion of textiles. Textiles with large primitive elements have high regularity and coarseness, whereas textiles with subtle primitive elements exhibit randomness and smoothness. Texture analysis results of the surface samples coincide well with those of display samples.     

Six-Fold Degenerate Dark States in a Four-Level Atomic System

With all driving fields on Raman resonance, a tripod-type atomic system quickly evolves into a dark state decoupled from the lossy excited level. The dark state depends strongly on field Rabi frequencies, spontaneous decay rates, and the initial atomic population in a complicated way. Analytical results reveal that it is a sixfold degenerate dark state with its three components superposed both coherently and incoherently due to population redistribution from spontaneous emission.     

Phase Dependence of the Inversionless Gain in a Λ System with Near—Degenerate Levels

Due to interaction with the vacuum of the radiation field,near-degenerate lower levels in a Λ system have an additional coherence term,the spontaneously generated coherence (SGC) term.For such a system,we investigate the effect of the relative phase between two coherent fields on the inversionless gain in the presence of the SGC.We find that the inversionless gain,which stems from both SGC and dynamically induced coherence,can be modulated by the relative phase.     

常见皮革的近红外光谱快速判别分析

皮革种类的鉴定对生产控制、贸易过程和市场管理都具有重要意义,目前尚未有皮革种类鉴定的正式检测标准,皮革种类鉴定主要依靠感官法、燃烧法、化学溶解法、显微镜法等综合判定,对人员要求高,主观性强。利用近红外光谱技术对市场五种常见皮革样品(头层牛皮革、剖层移膜革、羊皮革、再生革和人造革)进行分析,利用判别分析法(discriminant analysis, DA)结合标准正态变量变换(multiplicative signal correction,MSC)、多元散射校正(standard normal variate,SNV)、一阶微分(first derivative)、二阶微分(second derivative)等光谱预处理方法进行分类鉴别。结果显示：上述五种革类在同一空间中重叠严重,但是利用样本反面光谱数据可以轻易将人造革和其他革类进行区分,误判率为1.2%,余下四种天然或加工革类重叠稍显严重,在同一个空间内同时对四种革类区分效果不是很理想,两两分组的分类效果较好,误判率13%～17.9%。而不同的数据处理方法在不同的判别分析模型中带来的效果也不尽相同,未发现一种能持续稳定为模型提供优化效果的预处理手段。上述数据说明采用近红外手段对于皮革种类进行判别是具有可行性的,由于本次取样来自于市场上的皮包、皮衣、皮带等最终产品,已经过染色、压花、覆膜等各种复杂处理,可能对模型带来一定的影响,如果能采取一些手段,如扩大样本量等,减弱这些影响,应该能得到更满意的结果。     

改进人工蜂群算法优化ELM分类模型

针对极限学习机(Extreme Learning Machine,ELM)参数优化问题,提出改进人工蜂群算法(Improvement Artificial bee colony, IABC)优化ELM分类模型。算法采用解更新策略池代替固定不变的更新策略,将邻域搜索自适应化;优化侦察蜂搜索方式,利用Kent映射产生均匀性更优的初始随机数序列。在分类数据集中,将IABC-ELM分类模型同ELM、PSO-ELM分类模型进行对比实验。实验中,IABC-ELM模型取得了最佳的分类结果,得到了最低的输出权重范数。结果表明,IABC-ELM模型分类效果显著优于对比模型,证实了IABC算法优化ELM分类模型的有效性和优越性。