资源列表
数学常用算法C++版
- 陈必红 编写的《用C++语言编写的数学常用算法》光盘内容-prepared by the "C language commonly used to prepare the mathematical algorithm" CD-ROM
迷宫搜索
- 这是一个实现自动生成随机迷宫，并且自动实现从迷宫的入口到出口的路径搜索的一个Applet程序-This is an automatically generated random maze, and automatically from the entrance to the maze of export path of a search procedures Applet
seg_source
- 图像分割算法，主要有水平集算法，等等其他的算法。-image segmentation algorithm, the main level of algorithm, and so on the other algorithms.
09.数据拟合
- 数据拟合源程序，对很多点数据能根据提示，自动拟合成曲线，去自动拟合有很大的帮助-data fitting source of many of the points that data can be prompted to automatically be synthesized curve, automatically fitting to be of great help
图的基本操作
- 实现图的各种基本操作 图的建立 删除 查找 遍历-plans to achieve the basic operation of the plan is to establish delete you traverse
解线性的迭代法
- 这是计算方法中用的解线性方程的迭代法，具有很强的实用性！-This is the calculation method used for solving linear equations of the iterative method, and has a strong practical!
数字图象处理学VC++实现
- 其中包括图像压缩的基本编码方法如Huffman编码\\算术编码\\JPEG 2000\\H.261压缩编码标准\\小波变换编码\\运动估计算法\\视频图象采集的VC实现等.-including the basic image compression coding methods as Huffman coding \\ arithmetic coding \\ JPEG 2 000 \\ H.261 coding standard \\ Wavelet Transform Coding \\ m
改进的LZSS压缩算法
- 本文提出了LZSS压缩算法在进行文本压缩时存在的问题，并给出了解决方法。改进后的算法具有较高的压缩率，实验结果令人满意。 关键词：LZSS；数据压缩 -This paper presents a compression algorithm LZSS text compression during the question and gives a solution. Improved algorithm with a higher compression ratio, the experi
时间序列分析VC源码
- 时间序列分析，分析序列是否是 白色噪声，分析相关性，可以进一步判断序列的相关和自相关-time series analysis, whether the sequence is white noise, correlation analysis, further sequence of judgment and autocorrelation
关联规则挖掘数据生成源文件vc_ardata-vc
- 关联规则挖掘数据产生程序.VISUAL C++ 可产生满足要求的挖掘数据.-Data Mining Association Rules have procedures. VISUAL C can be produced to meet the requirements of data mining.
Skapura
- skapura数据挖掘源程序VISUAL C++ 采用图元格式处理中间数据,节省大量空间-skapura source data mining using Visual C map yuan handle intermediate data format, to save a lot of space
支持向量机的MATLAB工具箱
- 基于MATLAB的源SVM程序包，请试用-based on MATLAB source SVM package, please try