delphi xvid 编解码

x-y图解法求二元精馏塔理论塔板数 本文件是一个m文件,要在matlab环境下运行-x-y graphical method for binary distillation theoretical plate number of this document is a document m, the operating environment Matlab

公历，阴历转换源代码-calendar, the lunar calendar change source code

最小二乘法和主成分回归法对同一数据进行分析，比较其优缺点-Least square method and principal component regression analysis of the data on the same, compare their advantages and disadvantages

这是一段采用SRP-PHAT算法的声源定位程序。为了减小计算量，采用了SRC(STOCHASTIC REGION  CONSTRICTION) 策略可以大大减小时间复杂度，比基于网格的SRP-PHAT的方法快千倍以上。

大M单纯形线性规划问题求解。 很不错的基于basic的源代码啊-Large M simplex linear programming problem solving. Very good basic source code based on ah

对一个可排序数组A[]，从右到左扫描这个有序的字数组，直到遇到第一个小于等于A[]的元素，然后把A[]插在该元素的后边。基于递归思想，从底至上地实现这个算法，效率会更高，也就是使用迭代。给定n个可排序的元素构成的一个数组A[]，输出一个非降序排列的数组A[]。

资源描述用于遥感图像分类。其输入为几幅遥感图像，使用k-mean聚类方法对图像中的不同地形进行聚类分割，分类分割效果不错哦，，欢迎大家下载，一起进步，一起学习。代码是matlab编写，注释比较清晰，易读。希望对图像分割的同学有帮助。欢迎大家下载，一起进步，一起学习。

THE FINITE-DIFFERENCE TIME-DOMAIN (FDTD) PART IV The Perfectly Matched Layer (PML) Absorbing Boundary Condition -THE FINITE-DIFFERENCE TIME-DOMAIN (FDTD) PART IV The Perfectly Matched Layer (PML) Absorbing Boundary Condition

用C语言实现哈夫曼编码对文件进行压缩,并没有通过类来实现,只是用标准的C语言中结构实现的,代码内部说明比较详细,具体可以看代码,包括对文件的编码也解码.-C language of the document Huffman coding compression, and not through the categories to fruition, but the standard C language structure to achieve, and the internal code note in greater detail, the specific code can be seen, including the encoding of the document also decoder.

The Molgedey and Schuster decorrelation algorithm, having square mixing matrix and no noise . Truncation is used for the time shifted matrix, and it is forced to be symmetric . The delay Tau is estimated . The number of independent components are calculated using Bayes Information Criterion (BIC), with PCA for dimension reduction.-The Molgedey and Schuster decorrelation algorithm, having square mixing matrix and no noise . Truncation is used for the time shifted matrix, and it is forced to be symmetric . The delay Tau is estimated . The number of independent components are calculated using Bayes Information Criterion (BIC), with PCA for dimension reduction.