Optimal strategy of searching FPD weights scanning matrix using GA-PSO

This paper discusses a kind of optimal method used for searching flat panel display （FPD） scanning matrix. The method adopts bionic algorithm： genetic algorithm （GA） and particle swarm optimization （PSO） algorithm. The method using single GA is more time-consuming, and the search efficiency is low in later evolution; the PSO algorithm is easily falling into the local optimal solution and appears the premature convergent phenomenon. Hence, a hybrid approach of GAPSO is found to optimize the search for high grayscale weights scanning matrix. Finally in the acceptable time, it finds a weight scanning matrix （WSM） of 256 gray scales with Matlab, whose scanning efficiency reaches 94.73% and the linearity is very good.

Patch-based vehicle logo detection with patch intensity and weight matrix

A patch-based method for detecting vehicle logos using prior knowledge is proposed.By representing the coarse region of the logo with the weight matrix of patch intensity and position,the proposed method is robust to bad and complex environmental conditions.The bounding-box of the logo is extracted by a thershloding approach.Experimental results show that 93.58% location accuracy is achieved with 1100 images under various environmental conditions,indicating that the proposed method is effective and suitable for the location of vehicle logo in practical applications.

Drawing Weighted Directed Graph from It's Adjacency Matrix

This paper proposes an algorithm for building weighted directed graph, defmes the weighted directed relationship matrix of the graph, and describes algorithm implementation using this matrix. Based on this algorithm, an effective way for building and drawing weighted directed graphs is presented, forming a foundation for visual implementation of the algorithm in the graph theory.

Spatial weight matrix in dimensionality reduction reconstruction for microelectromechanical system-based photoacoustic microscopy

A micro-electromechanical system(MEMS)scanning mirror accelerates the raster scanning of optical-resolution photoacoustic microscopy(OR-PAM).However,the nonlinear tilt angular-voltage characteristic of a MEMS mirror introduces distortion into the maximum back-projection image.Moreover,the size of the airy disk,ultrasonic sensor properties,and thermal effects decrease the resolution.Thus,in this study,we proposed a spatial weight matrix(SWM)with a dimensionality reduction for image reconstruction.The three-layer SWM contains the invariable information of the system,which includes a spatial dependent distortion correction and 3D deconvolution.We employed an ordinal-valued Markov random field and the Harris Stephen algorithm,as well as a modified delay-and-sum method during a time reversal.The results from the experiments and a quantitative analysis demonstrate that images can be effectively reconstructed using an SWM;this is also true for severely distorted images.The index of the mutual information between the reference images and registered images was 70.33 times higher than the initial index,on average.Moreover,the peak signal-to-noise ratio was increased by 17.08%after 3D deconvolution.This accomplishment offers a practical approach to image reconstruction and a promising method to achieve a real-time distortion correction for MEMS-based OR-PAM.

Research on consistency measurement and weight estimation approach of hybrid uncertain comparison matrix

The consistency measurement and weight estimation approach of the hybrid uncertain comparison matrix in the analytic hierarchy process （AHP） are studied. First, the decision-making satisfaction membership function is defined based on the decision making＇s allowable error. Then, the weight model based on the maximal satisfactory consistency idea is suggested, and the consistency index is put forward. Moreover, the weight distributing value model is developed to solve the decision making misleading problem since the multioptimization solutions in the former model. Finally, the weights are ranked based on the possibility degree approach to obtain the ultimate order.

Correction to: Spatial weight matrix in dimensionality reduction reconstruction for micro-electromechanical system-based photoacoustic microscopy

Following publication of the original article[1],the keywords are missing in the article.Keywords:Photoacoustic microscopy,Spatial weight matrix,Dimensionality reduction,Distortion correction,Mutual information The original article has been updated.

Wide-Area Delay-Dependent Adaptive Supervisory Control of Multi-machine Power System Based on Improve Free Weighting Matrix Approach

The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).

基于Matrix Profile的时间序列分割技术改进

时间序列分割是数据挖掘领域中的一个重要研究方向.目前基于矩阵轮廓(matrix profile,MP)的时间序列分割技术得到了越来越多研究人员的关注,并且取得了不错的研究成果.不过该技术及其衍生算法仍然存在不足:首先,基于矩阵轮廓的快速低代价语义分割算法中对给定活动状态的时间序列分割时,最近邻之间通过弧进行连接,会出现弧跨越非目标活动状态匹配相似子序列问题;其次,现有提取分割点算法在提取分割点时采用给定长度窗口,容易得到与真实值偏差较大的分割点,降低准确性.针对以上问题,提出一种限制弧跨越的时间序列分割算法(limit arc curve cross-FLOSS,LAC-FLOSS),该算法给弧添加权重,形成一种带权弧,并通过设置匹配距离阈值解决弧的跨状态子序列误匹配问题.此外,提出一种改进的提取分割点算法(improved extract regimes,IER),它通过纠正弧跨越(corrected arc crossings,CAC)序列的形状特性,从波谷中提取极值,避免直接使用窗口在非拐点处取到分割点的问题.在公开数据集datasets_seg和MobiAct上面进行对比实验,验证以上两种解决方案的可行性和有效性.

Phosphorylation and biosynthesis of high molecular weight proteins of tumor nuclear matrix

Our previous studies showed a predominance of high molecular weight protein group in tumor nuclear matrices. Contrary to normal cells, proteins of this group are preferentially phosphorylated. Phosphoproteins of hepatoma nuclear matrix are selectively subjected to rapid proteolysis. By alkali treatment and a monoclonal antibody against phosphotyrosyl residue the presence of two high molecular weight bands of phosphotyrosyl-containing proteins was detected in nuclear matrices of tumor but not of normal liver cells. High molecular weight protein group of tumor nuclear matrices revealed also a rapid turnover and preferential incorporation of labeled amino acids selectively inhibited by chloramphenicol.

A Note on the Spectral Radius of Weighted Signless Laplacian Matrix

A weighted graph is a graph that has a numeric label associated with each edge, called the weight of edge. In many applications, the edge weights are usually represented by nonnegative integers or square matrices. The weighted signless Laplacian matrix of a weighted graph is defined as the sum of adjacency matrix and degree matrix of same weighted graph. In this paper, a brief overview of the notation and concepts of weighted graphs that will be used throughout this study is given. In Section 2, the weighted signless Laplacian matrix of simple connected weighted graphs is considered, some upper bounds for the spectral radius of the weighted signless Laplacian matrix are obtained and some results on weighted and unweighted graphs are found.

关于赋权非正则图的A_(α)特征值和特征向量

设G_(ω)=(G,ω)是一个赋权图,其邻接矩阵和赋权度对角矩阵分别A(G_(ω))和D(G_(ω))。对于α∈[0,1],G_(ω)的A_(α)-矩阵为A_(α)(G_(ω))=αD(G_(ω))+(1-α)A(G_(ω))。对于连通赋权非正则图G_(ω),给出了其关于A_(α)-特征值的一些界,并得到了A_(α)-谱半径对应的特征向量中最大分量与最小分量比值的下界。

基于现场可编程门阵列的矩阵求逆算法设计

由于自适应抗干扰算法在更新最优权值时存在时间延时,导致很难满足动态环境下的权值更新率要求。针对该情况已有学者对如何实现快速采样矩阵求逆算法进行研究,但仍存在只适用于低维矩阵,且权值更新率慢的问题。为解决上述问题,提出了一种基于Cholesky分解的采样矩阵求逆算法实现架构。该实现架构主要包括协方差矩阵计算模块、Cholesky分解模块、计算下三角矩阵L的逆矩阵模块、三角矩阵相乘和权值计算模块。设计采用流水线加状态机实现结构有效地解决了因高阶采样矩阵求逆运算量大产生的权值更新率慢的问题。仿真结果表明,在现场可编程门阵列(field programmable gate array,FPGA)的硬件平台上,对于56阶采样矩阵,在100 MHz工作频率下,一次权值的更新时间仅需要1.2 ms。本文所提的实现架构为自适应抗干扰快速求解权值提供了一种切实可行的解决方案,对存在类似需求的权值求解系统具有一定的参考价值。

加权信息量支持下融合InSAR形变特征的滑坡易发性评价

使用SBAS-InSAR处理六盘水市水城区2018-07~2019-08共69景Sentinel-1A卫星影像,获取地表形变作为动态评价因子,用于完善传统滑坡易发性评价研究缺乏动态特征数据应用的问题。结果表明,使用10种静态评价因子融合InSAR形变特征数据作为动态评价因子,在耦合层次分析法与信息量法的加权信息量模型下对比仅使用静态特征数据,ROC曲线下面积分别为0.756 02和0.888 68,模型性能提升约13.3%;再将历史灾害点叠加于2种分区图下检验分区精度,相比于未融入形变特征,融入形变特征可纠正约12.44%的误分类区域,能较好地提升分区的可靠性。

基于一致性的赋权方法在课程过程性评价中的应用

针对课程平时成绩的权重比例,构建采用客观赋权法确定权重的动态代数模型.基于平时成绩的各项得分,分析项目之间的一致度,应用矩阵理论对权重进行一致性检验,给出一致性最强的权重比例.结合实例计算最优权重.

基于加权非负矩阵分解的异常声音检测方法研究

异常声音检测方法多用强标签数据进行训练,而高质量的强标签音频数据标注难度较大、收集成本高昂。针对现有异常音频检测方法使用弱标签数据会受到非平稳和时变噪声的干扰,导致训练结果较差、准确率低的问题,提出一种基于音频频谱的加权非负矩阵分解WNMF方法。该方法使用WNMF对弱标签和无标签数据进行标记,并分离目标声音事件和背景噪声。在适当的权值下,WNMF改变标记时不同频段音频信息的重要性,以抑制噪声,提高分离质量,使其逼近全监督模型训练的效果;之后使用卷积神经网络产生帧级预测和音频标签预测。仿真实验结果表明,该方法的准确率相比于传统NMF处理弱标签数据的方法提升了4.8%。

基于Relief算法的不平衡数据分类分级算法仿真

不平衡数据的分类分级是保证大数据技术高效使用过程中不可缺少的环节,但分类分级过程易受数据属性、冗余性、不均衡性等问题的干扰。为解决上述问题,提出不平衡数据朴素贝叶斯分类分级算法。采用合成少数类过采样技术降低数据的不平衡度,通过距离相关系数与最大信息系数完成不平衡数据的特征选择与筛选,采用Relief算法对筛选的特征做权重分配,并输入到朴素贝叶斯模型中实现分类,再结合动态阈值算法完成数据的分级。实验结果表明,所提算法的运行时间短、分类精度高,能够有效提升数据处理效果。

企业研发经费的就业效应——基于制造业资本品上下游行业的空间计量分析

加大企业研发经费(R&D经费)投入会对就业产生何种影响是非常值得关注的问题。本文首先建立了基于研发而形成的资本品上下游行业模型,从理论上分析企业R&D经费对就业的影响。然后,基于我国2012—2021年制造业行业数据,运用空间计量的方法对企业R&D经费的就业规模总效应和上下游行业就业结构变化进行实证检验。研究发现:我国企业R&D经费对就业规模总效应不显著;但资本品上游行业企业R&D经费增加会负向影响下游行业就业,使上游行业就业占比增加,发生就业结构上迁。异质性分析表明,设备型上游行业组的就业结构上迁效应明显。机制分析表明,上游行业产品创新增加促进了下游行业的资本品使用,对下游行业劳动力产生替代,促使就业结构向上迁移。研究结论对优化创新和就业政策、减缓摩擦性失业有一定现实意义和参考价值。

加权区间值犹豫模糊集的群决策方法

为了在区间值犹豫模糊集(IVHFS)中体现出决策专家的重要性,把所有评审专家的综合权重注入IVHFS中,进而定义了加权区间值犹豫模糊集(WIVHFS).将WIVHFS用三维点坐标(由区间值隶属度的中位数、区间值隶属度的清晰度以及评审专家综合权重构成)进行刻画,在此基础上给出了加权区间值犹豫模糊元(WIVHFE)的相关运算;基于WIVHFE的相关运算采用熵值法计算测评准则客观权重,利用0-1优先关系矩阵来获取任意2个备选方案的总测评准则权重优势值与总测评准则权重劣势值,并依据二者之间的大小排序方案.最后,通过一个具体案例说明了文中理论与方法的可行性.

间接矩阵变换器-双异步电机调速系统的模型预测控制权重因数整定

间接矩阵变换器-双异步电机调速系统结构复杂,传统模型预测电压控制中权重因数整定困难。该文提出一种基于层次分析评估的权重因数整定方法,通过对物理量纲、双电机、网侧与电机侧统合将权重因数数量减少至1个,并引入层次分析评估法来实时调整权重因数以满足各种工况的要求,使系统在宽运行范围、多功率流模态下均具有良好的网侧电能质量与电机调速性能。通过仿真和实验证明,采用该文提出的方法,可保证在多种工况下网侧功率因数接近1,网侧电流正弦,电机定子电流畸变小、电机动态调速性能良好。而且,相比于传统的简化模型预测电压控制方法,该文所提出的方法权重因数整定简单易实现,网侧电流质量更好。

基于TFAHP的电炉企业多维一体化财务模式评价模型

电炉企业的财务由于其参数指标众多,对相关模式评价过程不能运用单一阈值理论,评价过程一直是个难题。设计基于TFAHP的电炉企业多维一体化财务模式评价模型。通过微观模拟电炉企业财务工资过程,确定评价指标,由此构建模糊评价矩阵,依据模糊评价矩阵,构建二级评价矩阵,在单一准则下计算各评价指标的相对权重,采用三角模糊数层次分析法确定总权重,由此构建评价模型,获取评价结果,设定评价等级集合及区间值,给出具体评语等级。实验可知,所构建模型进行多维一体化财务模式评价在电炉企业应用效果较好,评价效率较高。