MDS-MAP

LFM信号与BPSK信号相区别分析识别的程序(LFM脨脜 潞 脜脫毛BPSK脨脜 潞 脜脧脿脟酶 卤 冒 脰脦枚脢 露 卤 冒渭脛 鲁 脤脨貌)

里面包含了大量的matlab的应用实例，对初学者来说非常有用(Which contains a large number of matlab application, is very useful for beginners)

对图像进行旋转，拉伸，镜像对称等变换的整合示例，包含最近邻插值，双线性插值即双三线性插值的处理部分程序(Image rotate, stretch, mirror symmetry transformation of the integration example, contains the most recent neighbor interpolation, bilinear interpolation double tri-linear interpolation processing part of the program)

汽车悬架仿真建模，比较好，适合初学者学习(Simulation modeling of vehicle suspension, the better for beginners to learn)

orthogonal frequency division multiplexing

SAS统计分析 沉其君主编 详细说明了怎样使用sas软件来做数学分析,很好的资料哦，可以很快对SAS入手(Shen monarch editor SAS statistical analysis described in detail how to use the software to do mathematical analysis sas, good information Oh, you can quickly start on SAS)

用matlab对chirp信号进行了仿真，表现出了chirp信号的frft的峰值搜索，参数估计(Using matlab for chirp signal simulation, showing a peak search chirp signal frft, the parameter estimates)

马氏距离是一种有效地计算两个样本集之间相似度的算法（数据之间协方差距离），与欧式距离相比，它考虑了各种特征之间的联系。本实验旨在通过给出的样本数据，设计一个最小马氏距离分类器并对测试点进行分类，然后将其与最小欧式距离分类器进行比较，实验得出当协方差矩阵为单位阵时，最小马氏距离分类器将与最小欧式距离分类器等价。本实验还根据实验样本设计贝叶斯分类器进行分类，并与最小马氏距离分类器进行比较，比较两种分类器的分类效果。(Markov distance is an effective method to compute the similarity between the two samples (data covariance distance), compared with the Euclidean distance, which takes into account the link between different characteristics. This experiment aimed at through the given sample data, design a minimum Mahalanobis distance classifier and classify the test points, and then compare it with the minimum Euclidean distance classifier. Experimental results showed that when the covariance matrix is a unit matrix, minimum Mahalanobis distance classifier with the minimum Euclidean distance classifier equivalent.In this experiment, according to the experimental design of the Bias classifier, and compared with the minimum distance classifier, the classification results of the two classifiers are compared.)

说明：  基于lstm算法在MATLAB对短期风速进行预测(Based on LSTM algorithm, short-term wind speed was predicted in MATLAB)

说明：  A VARIATIONAL APPROACH TO REMOVE MULTIPLICATIVE NOISE