MATLAB

说明：  Hermite插值的MATLAB程序。需要的来下载。(Hermite interpolation of the MATLAB program. Need to download.)

对有类别监督的数据进行先行判别分析用于降维 数据为结构体类型，返回数据也是降维后的结构体类型。如(a.X a.y)a.X是带有类别的数据，a.y是类别信息(Synopsis: model = lda(data) model = lda(data,new_dim) Description: This function is implementation of Linear Discriminant Analysis. The goal is to train the linear transform which maximizes ratio between between-class and within-class scatter matrix of projected data.)

通过计算和作图，比较4PSK和QPSK这两种不同的编码方式之间的优略，说明发射信号一个是三值的一个是二值的(By calculating and plotting, preferably QPSK, and compare these two 4PSK encoding between different strategies, a description of the transmission signal is a ternary value is two)

Algorith PCA in Matlab. The example is basic, with random data

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CoSaMP算法，在重构信号时，选取两倍稀疏度的原子来恢复原始信号，再删去一倍稀疏度的原子。(CoSaMP algorithm, in the reconstructed signal, select twice the atomic sparsity to recover the original signal, and then deleting the double sparsity of atoms.)

此程序可用来对二维光子晶体带隙结构进行模拟绘图(This procedure can be used to two-dimensional photonic band gap structure to simulate the drawing)

简介：IFP_FCM,改进型FCM(模糊C均值)聚类算法,由Frank Hoppner与Frank Klawonn于2003年提出,解决了FCM算法对初始值设定较为敏感、训练速度慢、在迭代时容易陷入局部极小的问题。并附带了Box和Jenkins煤气炉数据模型辨识实例。 文件清单： IFP_FCM算法原始论文： Improved fuzzy partitions for fuzzy regression models.pdf 程序清单： IFP_FCM.m - IFP_FCM算法主函数 initifp_fcm.m - initifp_fcm子函数 stepifp_fcm.m - stepifp_fcm子函数 distifp_fcm.m - distifp_fcm子函数 IFP_FCM_T_S_box_test.m - IFP_FCM测试实例：Box和Jenkins煤气炉数据T-S模糊模型辨识 数据文件： box_data.mat - Box和Jenkins煤气炉数据(IFP_FCM, modified FCM (Fuzzy C-Means) clustering algorithm, in 2003, proposed by Frank Hoppner and Frank Klawonn, FCM algorithm to solve the initial value setting is more sensitive, slow training, while iterating easy to fall into local minimum problem. And comes with Box and Jenkins gas furnace model identification data instance.)

多边缘尺度 检测 已经调试运行成功了的哦 大家可以下载看啊看你 (Multi-scale edge detection has been successful commissioning of the download look ah Oh, we can see you)

本代码的方法是借助旋转不变技术估计信号参数(Estimation of Signal Parameters via Rotational Invariance Techniques)，现已成为谐波恢复（即正弦波个数及频率估计）的一种主要特征分解法。(This code is to help the estimated ESPRIT signal parameters (Estimation of Signal Parameters via Rotational Invariance Techniques), has now become the harmonic retrieval (that is, the number and frequency sine wave estimated) of one of the main characteristics of decomposition.)