ICACarNoiseVib

ALOHA算法的仿真，对于算法的过程用mutlab进行了仿真(Frame slot ALOHA algorithm simulation)

FilterTitleOverlay字幕叠加的filter(FilterTitleOverlay subtitles superimposed filter)

用Matlab实现空时分组编码对其MIMO系统性能进行分析得出理想的结果(Using Matlab realize their space-time block coding MIMO system performance analysis of the desired results)

说明：  3GPP LTE中上行虚拟MIMO比例公平调度算法的源程序代码(Virtual MIMO in 3GPP LTE uplink proportional fair scheduling algorithm source code)

matlab回归分析工具箱，用于数据处理和统计分析建模(regression analysis matlab toolbox for data processing and statistical analysis modeling)

神经网络源代码，一个字符识别程序，分别实现了没有噪声和带有噪声的测试(Neural network source code, a character recognition program, were achieved with no noise and noise tests)

LMS算法的MATLAB实现函数, 输入参数: xn 输入的信号序列 (列向量) dn 所期望的响应序列 (列向量) M 滤波器的阶数 (标量) mu 收敛因子(步长) (标量) 要求大于0,小于xn的相关矩阵最大特征值的倒数 itr 迭代次数 (标量)(LMS algorithm MATLAB realization function)

Histogram equalization matlab code

MATLAB和AForge.NET实现的神经网络模型源代码，有例子 ， 适合初学者 (MATLAB and AForge.NET realize neural network model source code, there are examples for beginners)

最小冗余最大相关性（MRMR）（MRMR.M） 需要外部库。详情请见MRMR。下载一个更新版本的互信息工具箱 偏最小二乘（PLS）回归系数（ReGCOEF.m） 使用MATLAB统计工具箱中的PLSReress ReliefF（分类）和RReliefF（回归）（ReleFracePr.M.） 从Matlab STATS工具箱中包装Releff.m。这是Matlab R2010B以后提供的。 ReliefF的另一个选择是使用ASU特征选择工具箱中的代码。这使用WEKA工具箱的ReleFEF，因此需要额外的库。请参阅相应的文档。 费雪评分（Fisher评分） 围绕ASFS特征选择工具箱围绕FSFisher。M(Minimum Redundancy Maximum Relevance (mRMR) (mRMR.m) Needs external library. See mRMR.m for details. Download a newer version of the mutual information toolbox Partial Least Squares (PLS) regression coefficients (regCoef.m) Uses plsregress.m from MATLAB statistics toolbox ReliefF (classification) and RReliefF (regression) (relieffWrapper.m) Wraps around relieff.m from the MATLAB stats toolbox. This is available MATLAB r2010b onwards. Another option for ReliefF is to use the code from ASU Feature Selection toolbox. This uses ReliefF from weka toolbox and hence needs additional libraries. Please see the corresponding documentation. Fisher Score (fisherScore.m) Wraps around fsFisher.m from the ASU Feature Selection toolbox)