CCE

文件是雷达设计使用的matlab源代码，其参考的是书籍《radar design with matlab》(document is designed to use radar Matlab source code, its reference books "radar design with Matlab")

标准粒子群算法，基于MATLAB环境下的实现(Standard particle swarm optimization algorithm in MATLAB)

利用函数MadHG生成规则LDPC码的校验矩阵H，其行重为6,列重为3,行数为列数一半(行数越大越好)，H中任意两列没有围长为4的圈，并得到H对应的生成矩阵G，可以保证mod(G*H ,2)=0。使用方法为:[H,G] = MadHG(m,n,x),x= 1(得到的G左半部分为单位阵) or 2(G右半部分为单位阵),(use function MadHG Generation rules LDPC check matrix H, re-6, series of three, out for a few half of the number (A bigger the better), H 2 arbitrary no girth of the four circles, H counterparts and with the formation of matrix G, we can be assured of mod (G* H, 2) = 0. To be used : [H, G] = MadHG (m, n, x), x = 1 (the G part of the Left Front units) or 2 (G right half of the units RUF),)

arma模型，利用matlab来实现的，arma模型的matlab代码实现。可以实现任意步数的预测。(arma model using matlab.You can achieve any number of steps predicted. )

泊松过程检验验证随机过程是否是泊松过程，运用算法对随机过程经进行检验(Poisson process inspection)

一系列展示图像压缩技术的源代码。包括有：使用块截断编码的图像压缩(Block Truncation)、基于高斯金字塔变换的图像压缩(Gaussian Pyramids)、基于离散余弦变换对图像压缩(Discrete Cosine Transform)、基于奇异值分解(SVD)的图像压缩(Singular Value Decomposition)。给出的代码还可以用于2D图像噪声消除。(Image Compression A collection of simple routines for image compression using different techniques. BTCODE: Image compression Using Block Truncation Coding. PYRAMID: Image compression based on Gaussian Pyramids. DCTCOMPR: Image compression based on Discrete Cosine Transform. IMCOMPR: Image compression based on Singular Value Decomposition. The given codes can be also used in 2D noise suppression. Notes: The function "conv2fft" performs a 2D FFT-based convolution. Type "help conv2fft" on Matlab command window for more informations.)

matlab source code from mathworks

主要介绍matlab中simulink的使用情况，里面图标的介绍以及如何画出模块图(Matlab simulink introduced in the usage of the icons inside, and how to draw block diagram)

说明：  RNA二级结构预测，比对，结构构象比对以及聚类。(RNA secondary structure prediction, comparison, structural conformation and clustering than.)

uci数据集 第一列为类标,其他列为特征(This is UCI dataset.The first column is label.The other columns are features.)