资源列表
k-means
- 数据挖掘算法源代码 k-means聚类算法的C#代码-Source code data mining algorithms k-means clustering algorithm C# code
递归程序输出
- 任意给定输入的一个小写英文字符串a1a2a3…an-1an (n≥5) 输出：字符串Ana1An-1a2An-2a3…A2an-1A1an,其中Ai为ai的大写形式 例如，输入aybdx，则递归程序输出XaDyBbYdAx -Any given input of a lowercase string a1a2a3 ... an-1an (n ≥ 5) Output: the string Ana1An-1a2An-2a3 A2an-1A1an, which Ai ai uppe
tstem.mstem
- 自绘图函数 数字信号处理时域绘图 丁玉美-time stem tstem mstem-Since the mapping function when the domain of digital signal processing graphics Ding Yumei-time stem tstem mstem
matlabduoyuanxinxironghe
- 此程序是针对文献《基于相关函数的多振动信号数据融合方法》撰写的matlab程序，属于多源信息融合-This program is for literature, " based on the relevant multi-function vibration signal data fusion," wrote the matlab program, part of multi-source information fusion
huffman用c语言扫描一幅bmp256色图像，利用哈夫曼对其进行编码
- 用c语言扫描一幅bmp256色图像，利用哈夫曼对其进行编码，并做出效率计算等-C language with a bmp256 color image scanner, using Huffman code it, and make efficient computing
apriorikmeans
- Jsp数据挖掘，对apriori+kmeans的实现,需要这方面的朋友们可以参考一下-apriori+kmeans buile on Jsp
Jsp(aprioriandkmeans)
- Jsp数据挖掘(apriori+kmeans)源代码。java语言编写，可连接sql-Jsp Data Mining (apriori+ kmeans) source code. java language can connect sql
AlgorithmDesignChapter4Chapter5
- 《计算机算法设计与分析》王晓东版本第四章五章课后习题的部分答案，百分百全对。C文件的格式。- Computer Algorithm Design and Analysis, Wang Xiaodong version of Chapter IV of five chapters of part of the answer after-school exercises, the whole hundred percent right. C file format.
bifurcation2dmap
- 混沌与分岔的小程序，是用matlab编写的，挺有用的-Chaos and Bifurcation of small procedures, are prepared using matlab, very usefull
在MATLAB上用于产生WCDMA 仿真信号源的源程序
- 在MATLAB上用于产生WCDMA 仿真信号源的源程序-In MATLAB on WCDMA simulation used to produce the source signal source
monte蒙特卡罗求圆周率算法
- 蒙特卡罗求圆周率算法，可以对蒙特卡罗算法有个初步认识，本程序C++实现-Monte Carlo algorithms for pi, the Monte Carlo algorithm can have a preliminary understanding, this procedure C++ Achieve
c++实现的KNN库:建立高维度的K-d tree
- c++实现的KNN库:建立高维度的K-d tree,实现K邻域搜索，最小半径搜索-K-NN algorithm implementation. It supports data structures and algorithms for both exact and approximate nearest neighbor searching in arbitrarily high dimensions.