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  • For the incomplete methods, we kept the representation of the queens by a table and the method of ca

    For the incomplete methods, we kept the representation of the queens by a table and the method of calculation to determine if two queens are in conflict, which is much faster for this kind of problems than the representation by a Matrix. heuristics: descent. Tests: 100 queens in less than 1 second and 67 iterations. 500 queens in 1 second and 257 iterations. 1000 queens in 11 seconds and 492 iterations. heuristics: Simulated annealing. Tests: 100 queens in less than 1 second and 47 iterations. 500 queens in 5 seconds and 243 iterations. 1000 queens in 13 seconds and 497 iterations. heuristics: based on Simulated Annealing. Tests: 100 queens in less than 1 second and 60 iterations. 500 queens in 1 second and 224 iterations. 1000 queens in 5 seconds and 459 iterations. 10 000 queens in 20 minutes 30 seconds and 4885 iterations.

    标签: the representation incomplete methods

    上传时间: 2015-05-05

    上传用户:1159797854

  • The module LSQ is for unconstrained linear least-squares fitting. It is based upon Applied Statisti

    The module LSQ is for unconstrained linear least-squares fitting. It is based upon Applied Statistics algorithm AS 274 (see comments at the start of the module). A planar-rotation algorithm is used to update the QR- factorization. This makes it suitable for updating regressions as more data become available. The module contains a test for singularities which is simpler and quicker than calculating the singular-value decomposition. An important feature of the algorithm is that it does not square the condition number. The Matrix X X is not formed. Hence it is suitable for ill- conditioned problems, such as fitting polynomials. By taking advantage of the MODULE facility, it has been possible to remove many of the arguments to routines. Apart from the new function VARPRD, and a back-substitution routine BKSUB2 which it calls, the routines behave as in AS 274.

    标签: least-squares unconstrained Statisti Applied

    上传时间: 2015-05-14

    上传用户:aig85

  • 《精通MATLAB7.0混合编程》系统地介绍MATLAB 7.0的混合编程方法和技巧。全书共分为13章。第1章和第2章介绍MATLAB的基础知识

    《精通MATLAB7.0混合编程》系统地介绍MATLAB 7.0的混合编程方法和技巧。全书共分为13章。第1章和第2章介绍MATLAB的基础知识,第3章简要介绍MATLAB混合编程,第4章至第9章分别介绍几种典型的混合编程方法,包括C-MEX、MATLAB引擎、MAT数据文件共享、Mideva、Matrix和Add-in。第10章、第11章介绍MATLAB与Delphi和Excel的混合编程。第12章介绍MATLAB COM Builder,第13章以图像处理为例介绍了一个综合应用实例。 本书按混合编程的具体方法进行逻辑编排,自始至终用实例描述,每章着重阐述各种混合编程方法的实质和要点,同时穿插了作者多年使用MATLAB的经验和体会。本书既适合初学者自学,也适用于高级MATLAB用户,可作为高等数学、计算机、电子工程、数值分析、信息工程等课程的教学参考书,也可供上述领域的科研工作者参考。 这里是本书所有源码压缩包,内容详尽、实例丰富,包含MATLAB实例的源文件、函数/命令和注解以及程序实例。

    标签: MATLAB 7.0 混合编程

    上传时间: 2013-12-19

    上传用户:1051290259

  • 实验描述:分布式数据库的算法partition的具体实现。即通过该算法找到关系数据库最优分裂点

    实验描述:分布式数据库的算法partition的具体实现。即通过该算法找到关系数据库最优分裂点,使得结果最优。 算法思想: 1、 首先根据所输入的attribute usage Matrix得到AQ( ) 2、 对CA矩阵中划分点预先设在n-1处,并将属性列分成两个集合,TA和BA,TA中的元为:{ A1 、A2 …… An-1 },BA中的元素为:{ An} 3、 确定集合TQ、BQ和OQ,其中TQ={ qj| AQ(qi) TA},BQ= TQ={ qj| AQ(qi) BA}, OQ=Q-{TQ BQ}。 4、 计算出CTQ、CBQ、COQ这些值,其中CTQ= ,CBQ= ,COQ= 5、 通过划分点的第次移动分别计算出z=CTQ*CBQ-COQ2 6、 对取到的z的最大值处标记,为分割点 7、 对CA进行调整,重复计算得到最终z的最大值点,对CA矩阵进行划分 8、 对上述算法进行修改,将得到的最大z值的分割点和次大的分割点都记录下来,得到两个分割,则将原有的属性集划分成三部分。 该算法的目的是找到独立存取的属性集合或者分别的应用集。比如说,如果可以找到两个属性A1,A2,他们只是被q1读取,而A3,A4被q2,q3读取,这样在分裂的时候可以确定。算法就是找到这些组。另外为了简单化起见,我命令refj(qi)全部等于1.

    标签: partition 算法 实验 分布式数据库

    上传时间: 2015-06-04

    上传用户:13160677563

  • 实验描述:分布式数据库的算法partition的具体实现。即通过该算法找到关系数据库最优分裂点(2个)

    实验描述:分布式数据库的算法partition的具体实现。即通过该算法找到关系数据库最优分裂点(2个),使得结果最优。 1、 首先根据所输入的attribute usage Matrix得到AQ( ) 2、 对CA矩阵中划分点预先设在n-1处,并将属性列分成3个集合,TA和BA和MA, 3、 确定集合TQ、BQ,MQ和OQ,其中TQ={ qj| AQ(qi) TA},BQ= TQ={ qj| AQ(qi) BA}, MQ={ qj| AQ(qi) MA},OQ=Q-{TQ BQ}。 4、 计算出CTQ、CBQ、CMQ、COQ这些值,其中CTQ= ,CBQ= ,CMQ= ,COQ= 5、 通过划分点的第次移动分别计算出z=CTQ*CBQ*CMQ-COQ3 6、 对取到的z的最大值处标记,为分割点 7、 对CA进行调整,重复计算得到最终z的最大值点,对CA矩阵进行划分 对上述算法进行修改,将得到的最大z值的分割点和次大的分割点都记录下来,得到两个分割,则将原有的属性集划分成三部分。

    标签: partition 算法 实验 分布式数据库

    上传时间: 2015-06-04

    上传用户:515414293

  • 寻找函数的全局极小值

    寻找函数的全局极小值,global minimization of contrast function with random restarts the data are assumed whitened (i.e. with identity covariance Matrix). The output is such that Wopt*x are the independent sources.

    标签: 函数 全局

    上传时间: 2013-12-15

    上传用户:康郎

  • Included are the files wav1.m, wav2.m, wavecoef.mat and readme. wav2 function implements the tree

    Included are the files wav1.m, wav2.m, wavecoef.mat and readme. wav2 function implements the tree structured wavelet transform of the input Matrix, up to the given level of decomposition. Wav2 uses another function called wav1, which takes the well known wavelet transform of the given Matrix. Daubechies wavelet coefficients are used for wavelet transform operation wahich is saved in wavcoeff.mat.

    标签: implements the wav Included

    上传时间: 2015-06-23

    上传用户:爱死爱死

  • 使用pso求最小化一函數 matlab程式碼

    使用pso求最小化一函數 matlab程式碼,寫的非常簡潔(不到100行),且還包括了2維的圖形展示,和大家分享參考!!! 一起學習matlab和各種optimize methods 最小化:(x-15)^2+(y-20)^2 The swarm Matrix is swarm(index, [location, velocity, best position, best value], [x, y components or the value component]) Author: Wesam ELSHAMY (wesamelshamy@yahoo.com) MSc Student, Electrical Enginering Dept., Faculty of Engineering Cairo University, Egypt

    标签: matlab pso 程式

    上传时间: 2013-12-18

    上传用户:zhaiye

  • 平均因子分解法

    平均因子分解法,适用于正定矩阵First, let s recall the definition of the Cholesky decomposition: Given a symmetric positive definite square Matrix X, the Cholesky decomposition of X is the factorization X=U U, where U is the square root Matrix of X, and satisfies: (1) U U = X (2) U is upper triangular (that is, it has all zeros below the diagonal). It seems that the assumption of positive definiteness is necessary. Actually, it is "positive definite" which guarantees the existence of such kind of decomposition.

    标签: 分解

    上传时间: 2013-12-24

    上传用户:啊飒飒大师的

  • unix或linux下的DNA分析软件源码 其功能如下 1. Edit up to 256 peptide or DNA sequences simultaneously. 2. Transla

    unix或linux下的DNA分析软件源码 其功能如下 1. Edit up to 256 peptide or DNA sequences simultaneously. 2. Translates DNA->protein click next to display next frame. 3. Dot Matrix plot of any 2 sequences. 4. Rudimentary amino acid statistics (MW and amino acid percentage) 5. Saves Matrix plot as PBM image format. 6. Sequence reversal. 7. Creates alignment file for highlight (below). 8. Tab key toggles editing of next sequence.

    标签: simultaneously DNA sequences Transla

    上传时间: 2013-12-13

    上传用户:lwwhust