基于阵灰色关联分析的仿真模型验证方法研究

针对常规灰色关联分析仅考虑时间序列之间的相似性,忽略时间序列之间的接近性,而导致基于常规灰色关联分析的模型验证存在一定风险的问题,提出了一种阵灰色关联度模型,综合了时间序列之间的相近性和相似性两个方面,可以处理具有多个特征行为的关联分析问题。证明了阵灰色关联度模型满足灰色关联四定理。给出了基于阵灰色关联分析的模型验证操作过程。最后,通过实例分析验证了改进模型的合理性和有效性。

加权阵灰色关联理论及其在仿真模型验证中的应用

常规灰色关联分析应用于仿真模型验证时,仅考虑了时间序列之间的相似性,忽略了时间序列之间的接近性,但这种接近却属于仿真模型的误差范畴,因此使用常规灰色关联分析进行仿真模型验证存在一定的风险,针对这一问题,提出了一种加权阵灰色关联度模型,综合了时间序列之间的相近性和相似性两个方面,因此提高了模型验证的准确性和可靠性,同时该模型可以同时处理具有多个特征行为的关联分析问题,给出了具体的基于加权灰色关联分析的模型验证的操作过程,并证明了改进模型满足灰色关联四定理。通过实例分析验证了改进模型的合理性和有效性。

基于相对形状上下文的低分辨率遥感影像阵群目标关联算法

目标关联是遥感影像融合处理的重要步骤,本质上是目标配对问题。针对低分辨率遥感影像中阵群目标的特点,提出了一种基于点模式匹配的阵群目标关联算法。首先提出一种新的基于点集的不变特征——相对形状上下文特征,然后建立了以相对形状上下文特征的统计检验匹配测度为基础的阵群目标关联数学模型。为了求解该模型,在构造新的相容性度量函数来初始化关联概率矩阵后,利用松弛标记法通过迭代逐步更新关联概率矩阵,同时通过行列双向正则化最终得到满足一对一约束的最优关联匹配结果。通过仿真和实际数据实验验证了新算法的有效性和鲁棒性。

易矩阵与Hadamard矩阵

易矩阵与Ｈａｄａｍａｒｄ矩阵王俊龙在文［１］中笔者给易矩阵下了一个恰当的定义，同时也设定了易矩阵的加法和乘法运算规则。易矩阵理论的建构主要是结合易图衍生的实际需要而产生的，文［２］已显示这种新型的易矩阵在易图设计中的优越作用。严格说来，易矩阵与通常的...

一类不确定多变量系统的稳定条件

本文利用微分方程解的估计及大系统关联阵的方法，对一类不确定多变量线性系统：ｘ＝ＤＡｘ，（这里Ｄ是不确定对角分块阵）作了分析。

COUPLING MODEL OF EXTENDED MANUFACTURING ORGANIZATION AND ITS APPLICATION

For the feature of complex weapon manufacturing on internet,a coupling model is proposed.By using the model,the correlation between manufacturing cells in an extended manufacturing organization can be evaluated quantitatively,so an appropriate control plan is determined.A strategy to improve and reduce the coupling relationship of the organization is studied.A correlation matrix of extended tasks is built to analyze the relationship between sub-tasks and manufacturing resources.An optimization method for manufacturing resource configuration is presented based on the coupling model.Finally,a software system for analyzing coupling model about manufacturing organization on internet is developed,and the result shows that the coupling model is effective.

Optimization of fault management system in power plants based on DD-RCM and TPN

A method of optimizing the fault management system in power plants based on DD-RCM （resultchain based modeling for digital developing） and TPN （temporal Petri net） is proposed. First, the model of the fault management system was set using DD-RCM. Then, it was transformed to the temporal Petri net model by corresponding rules. Secondly, relationships among all the activities, such as choice, conflict, synchronization and concurrency, were confirmed according to the Petri net model and described employing the reengineering algorithm of incidence matrix. Thirdly, the Petri net model was reduced by combining reduction rules and conflict, synchronization relationships to optimize the fault management system in power plants. Finally, the functionality of the reduced net was proved by the temporal logic of the temporal Petri net.

用行列式性质对有关网络拓扑结论的证明

本文提出:(一)用行列式的基本性质直接证明不定导纳阵列式各元代数余子式都相等的方法,(二)用分块行列式证明A_i、A_j大子式积公式的简单方法。由于直接用基本性质,因而过程直观简单,教师易教,学生非常容易接受。

海伦县玉米种植区域确定的探讨

本文采取模糊数学的原理和方法,运用电子计算机模糊聚类分析程序,以年平均气温、有效积温、年平均降雨量、无霜期、光照时数、有效氮、磷、钾为聚类因素,以海伦县二十八个乡镇为聚类单元,确定了适宜玉米种植的四个区域及与之相适应的玉米品种,实现了对玉米生产的宏观调控,为研究玉米的生长发育规律和高产栽培技术措施,提供了科学依据。

Applications of Graph Theory to Gross Error Detection for GPS Geodetic Control Networks

This paper describes a broad perspective of the application of graph theory to establishment of GPS control networks whereby the GPS network is considered as a connected and directed graph with three components.In this algorithm the gross error detection is undertaken through loops of different spanning trees using the "Loop Law" in which the individual components Δ X, Δ Y and Δ Z sum up to zero.If the sum of the respective vector components ∑X,∑Y and ∑Z in a loop is not zero and if the error is beyond the tolerable limit (ε>w),it indicates the existence of gross errors in one of the baselines in the loop and therefore the baseline must be removed or re_observed.After successful screening of errors by graph theory,network adjustment can be carried out.In this paper,the GPS data from the control network established as reference system for the HP Dam at Baishan county in Liaoning province is presented to illustrate the algorithm.

A NOVEL APPROACH FOR DOA ESTIMATION IN UNKNOWN CORRELATED NOISE FIELDS

The key of the subspace-based Direction Of Arrival (DOA) estimation lies in the estimation of signal subspace with high quality. In the case of uncorrelated signals while the signals are temporally correlated, a novel approach for the estimation of DOA in unknown correlated noise fields is proposed in this paper. The approach is based on the biorthogonality between a matrix and its Moore-Penrose pseudo inverse, and made no assumption on the spatial covariance matrix of the noise. The approach exploits the structural information of a set of spatio-temporal correlation matrices, and it can give a robust and precise estimation of signal subspace, so a precise estimation of DOA is obtained. Its performances are confirmed by computer simulation results.

An Improved Direction Relation Detection Model for Spatial Objects

Direction is a common spatial concept that is used in our daily life. It is frequently used as a selection condition in spatial queries. As a result, it is important for spatial databases to provide a mechanism for modeling and processing direction queries and reasoning. Depending on the direction relation matrix, an inverted direction relation matrix and the concept of direction pre- dominance are proposed to improve the detection of direction relation between objects. Direction predicates of spatial systems are also extended. These techniques can improve the veracity of direction queries and reasoning. Experiments show excellent efficiency and performance in view of direction queries.

On the p-norm joint spectral radius

The p-norm joint spectral radius is defined by a bounded collection of square matrices with complex entries and of the same size. In the present paper the author investigates the p-norm joint spectral radius for integers. The method introduced in this paper yields some basic formulas for these spectral radii. The approach used in this paper provides a simple proof of Berger-Wang' s relation concerning the ∞-norm joint spectral radius.

A matching algorithm based on hybrid matrices consisting of reference differences and disparities

Unique correct correspondence cannot be obtained only by use of gray correlation technique, which describes gray similar degree of feature points between the left and right images too unilaterally. The gray correlation technique is adopted to extract gray correlation peaks as a coarse matching set called multi-peak set. The disparity gradient limited constraint is utilized to optimize the multi-peak set. Unique match will be obtained by calculating the correlation of hybrid matrices consisting of reference differences and disparities from the multi-peak set. Two of the known corresponding points in the left and right images, respectively, are set as a pair of reference points to determine search direction and search scope at first. After the unique correspondence is obtained by calculating the correlation of the hybrid matrices from the multi-peak set, the obtained match is regarded as a new reference point till all feature points in the left (or right) image have been processed. Experimental results proved that the proposed algorithm was feasible and accurate.

E(s^2)最优超饱和设计与BIB设计的对等关系

证明了大小为 (n ,m) =( 2k + 2 ,t( 2k + 1 ) ) (k≥ 2 ,t≥ 2 ,且当k为偶数时 ,t亦为偶数 )的E(s2 )最优超饱和设计与BIB设计的对等关系 ,使得可以通过构造BIB设计来寻求E(s2 )

基于CMTMV的多变量时变扰动系统性能评估

本文提出了基于左右对角关联阵的多变量时变最小方差(combined left/right diagonal interactors multivariable time-variant minimum variance,CMTMV)多扰动系统性能评估方法.首先,将左右对角关联阵引入多变量系统,来表征输入输出时滞结构,根据不同扰动作用时间设计CMTMV控制器,结合多模型混合权重的思想设计多模型CMTMV控制器.然后,利用多模型CMTMV控制器得出各被控变量输出方差,将多模型CMTMV控制器下被控变量的平均方差作为性能评估的基准.最后,本文通过在数值仿真和重油分馏过程中的控制系统性能评估的应用,验证了CMTMV评估方法的有效性.

Completely Positive Realizations of a Cycle

An n × n real matrix A is called doubly nounegative, if A is entrywise nonnegative and semidefmite positive as well. A is called completely positive if A can be factored as A=BBt,where B is some nonnegative n × m matrix. The smallest such number m is called the factorization index (or CP-rank) of A. This paper presents a criteria for a doubly nonnegative matrix realization of a cycle to be completely positive, which is strightforward and effective.

Smith normal forms of incidence matrices

A brief introduction is given to the topic of Smith normal forms of incidence matrices. A general discussion of techniques is illustrated by some classical examples. Some recent advances are described and the limits of our current understanding are indicated.

Fusion Method for Interval Number Multi-sensor Information

The interval numbers are used to types and observation of sensors, a new fusion represent the characteristic values of object method for multi-sensor object recognition is proposed from the viewpoint of decision making theory. The method defines the distance matrix and grey association matrix between all object types and unknown object. After solving the optimization problem of maximizing the standard deviations for all attributes, the weights of the attributes are obtained. Thus, the result of recognition for the unknown object is given by the grey association degree. This method avoids the subjectivity of selecting attributes weights. It is straightforward and can be performed on computer easily. The simulated example demonstrates the feasibility and effectiveness of the proposed method.

On region crossing change and incidence matrix

In a recent work of Ayaka Shimizu, she studied an operation named region crossing change on link diagrams, which was proposed by Kishimoto, and showed that a region crossing change is an unknotting operation for knot diagrams. In this paper, we prove that the region crossing change on a 2-component link diagram is an unknotting operation if and only if the linking number of the diagram is even. Besides, we define an incidence matrix of a link diagram via its signed planar graph and its dual graph. By studying the relation between region crossing change and incidence matrix, we prove that a signed planar graph represents an n-component link diagram if and only if the rank of the associated incidence matrix equals c n + 1, where c denotes the size of the graph.