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说明：  利用二维小波的图像增强 基于小波变换的多尺度图像边缘检测matlab源代码(在Matlab7.0下运行) (Using two-dimensional wavelet image enhancement based on wavelet transform multi-scale edge detection matlab source code (in Matlab7.0 run))

有关matlab的实验的结果和分析以及部分源代码(The results of experiments on matlab and analysis, and part of the source code)

以前使用matlab和vc混合编程都使用的是先将m程序用mcc转化成dll，再在vc中调用 的方法。这种方法对比较复杂的m文件很方便，但是对一些小的程序，如曲线可视化、计算矩阵特征值等，对这些只需要一两行代码的小程序，再使用dll就得不偿失了。经过试验后，发现可以直接在C++程序中调用matlab c/c++ math & graphic library的函数。(before using Matlab and vc mixed programming using the first procedure used mcc m into dl l, then vc call method. This method of complex documents m very easy, but for some minor procedures, such as curve visualization, matrix eigenvalue calculation, and so on, these are just two lines need a small procedure code, reuse dll on the loss outweighs the gain. After testing, can be found directly in the C Programming Calling Matlab c/c math)

用MATLAB的脚本语言M语言编写的，用于在MATLAB环境下实现帕笛近似（高阶模型简化降阶）的程序源代码，可以在MATLAB环境下直接运行。(MATLAB M scripting language language, MATLAB environment for the realization of Palau under Di approximation (high-order model to simplify Reduction) program source code, in the MATLAB environment direct operation.)

感应双馈发电机系统的仿真，大学数值分析算法，实现典型相关分析，用于信号特征提取、信号消噪，包括AHP，因子分析，回归分析，聚类分析，包含位置式PID算法、积分分离式PID，时间序列数据分析中的梅林变换工具，使用混沌与分形分析的例程。( Simulation of doubly fed induction generator system, University of numerical analysis algorithms, Achieve canonical correlation analysis, For feature extraction, signal de-noising, Including AHP, factor analysis, regression analysis, cluster analysis, It contains positional PID algorithm, integral separate PID, Time series data analysis Mellin transform tool, Use Chaos and fractal analysis routines.)

mimo系统注水算法。。。。。。。。。。。。。。。。。。。。。。。。。。。(mimo systems injection method. . . . . . . . . . . . . . . . . . . . . . . . . . .)

opencv3.0实现的卡尔曼滤波鼠标移动预测(the sourse of kalman)

Parsevals Relation and Relations between the DFTs of the Periodic Even and Odd Parts of a Real Sequence

本代码为粒子群基本算法代码，其在建模上面的贡献显著，很大程度上都能够优化建模解决方案。(Particle Swarm Optimization)

The source code used here is useful for evaluating the degree of the bspline