Mxulie

这个matlab代码是用维纳滤波得到的运动场。(The motion field is obtained from Wiener filtering in matlab code.)

该程序实现D-S论据的数据融合功能，针对具体问题只需要修改其中的参数即可。(DS arguments to achieve the program s data fusion capabilities, aimed at specific issues which only need to modify the parameter.)

face detection by matlab

二次插值法优化，有简单说明，并有一例子。希望大家喜欢(Optimize the second interpolation method, there is a brief description, and there is one example. I hope everyone likes)

随机序列产生程序(用乘同余法产生随机数)(random sequences generated (by using the same method I have a random number))

基于matlab编写的源码 做简单的数字识别(Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification)

matlab 界面编程代码 范例程序很多(matlab interface procedures, many examples of programming code)

支持向量机的研究现已成为机器学习领域中的研究热点，其理论基础是Vapnik[3]等提出的统计学习理论。统计学习理论采用结构风险最小化准则，在最小化样本点误差的同时，缩小模型泛化误差的上界，即最小化模型的结构风险，从而提高了模型的泛化能力，这一优点在小样本学习中更为突出。SVM理论正是在这一基础上发展而来的，经过十几年的研究和发展，已开始逐步应用于一些领域。在解决小样本、非线性及高维模式识别问题中表现出许多特有的优势，已经在模式识别、函数逼近和概率密度估计等方面取得了良好的效果。( Support Vector Machine (SVM) is a new machine learning technique in recent years developed based on statistical learning theory (SLT). It wins popularity due to many attractive features and emphatically performance in the fields of nonlinear and high dimensional pattern recognition. The theory and algorithm of SVC is studied at first, then, simulation is to recognize handwritten numeral with the Lib-SVM toolbox. At last, we study the result, which shows that the SVC can do the classification problem with good performance, shorter operation time and is more suitable for real-time implementation.)

通过Matlab求出连续时间信号的傅立叶变换及编程绘制各种连续时间信号系统的时域波行，幅度谱以及相位谱(Fourier transform of continuous-time signal obtained through Matlab and programming time domain wave line to draw a variety of continuous-time signal system , the amplitude spectrum and phase spectrum )

高斯函数应用很广泛，因其各列良好的不相干性等特点，被广泛应用到压缩感知等领域(Gaussian function is widely used, because of its good irrelevant columns, etc., are widely applied to areas such as compressed sensing)