参数均衡在 TMS320C6000 DSP

奇数N 阶魔方阵问题： 奇数N 阶魔方阵的构造规则如下： 1、在第一行的正中间填入1； 2、如果左上角能够移动，则往左上角填入后继的数；如果左上角不 能移动，则顺移到该列最下方左边的一列中最靠近该列的位置； 3、如果左上角不能移动，同时在该列位置的最下方左边最靠近的位 置处也不能填入数，则往该位置的上一行的最右边的位置处填入 后继数； 4、每次尽可能地往左上角填数，如果发现左上角已经填满了数，则 从当前填的数的位置下方填上后继数。 要求： 无。 输入： 用户从键盘任意输入一个正奇数。 输出： 打印出该魔方阵。-odd N bands Demon Lineup : N-odd magic Lineup Construction Rules are as follows : 1, the first line is the middle of a preference; Two, if the upper left corner to Mobile, the successor to fill in the upper left; If the upper left corner, unable to move, with the move out of the bottom of the left one of the closest out of position; three, if the upper left corner, unable to move, while in the position shown in the bottom left nearest location Department has not entered a few, to the position of the party on the right side of the positions filled successor; 4, each possible to fill the upper left corner, if fill the upper left corner, has found a few, from the current fill several positions to fill in the bottom subsequent few. Requ

用matrix A(8,10) 定义数组，就可以像在matlab里一样引用数组元啦！

求取任意精度pi值-arbitrary precision strike pi value

应用背景Implement k-means clustering on a training data set  to predict classification values of a test data set.关键技术The experiment intended to classify test data values using the data   mining strategy known as k-means clustering.   The 6 variables in the training data are used to plot the data and   centroids are placed to locate clumps of the 255, classified training   data. Once located, a classification value can be assigned to the 100,   test data. 

DXF轨迹图转G代码，有 直线，圆，圆弧，样条曲线，优化多段线，多段线。与下位机串口通讯！只有一些基本的功能，离实际应用还有距离，但可以作为参考代码，还是有一定的借鉴意义的！注意注册串口控件，要不然不能运行的起来

指派问题的匈牙利解法，从文件中读入待指派的数据。-Assignment problem of the Hungarian method, read from a file to be assigned to data.

数据挖掘是信息产业界近年来非常热门的研究方向，聚类分析是数据挖掘中的核心技术。本文对数据挖掘领域的聚类分析方法及代表算法进行分析，并从多个方面对这些算法性能进行比较，同时还对聚类分析在数据挖掘中的几个应用进行了阐述。-Data Mining is the IT industry is very popular in recent years the direction of the research, cluster analysis is data mining in the core technology. In this paper, the field of data mining methods and the representative of cluster analysis algorithm analysis, and from several aspects of these algorithms to compare the performance, but also on the cluster analysis of data mining in several applications are described.

svm实现的例子-SVM realize examples

摄影测量中将数据读入，进行空间外方位元素的计算和控制测量点的确定-Photogrammetry data will be read, space orientation element of calculation and measurement control points identified