Trend-test model

说明：  自编的快速小波变换mallat算法，使用‘db1’小波函数，在卷积时使用wkeep命令进行了数据截取。重构信号和原信号比较误差较小。(self fast wavelet transform Mallat algorithm, the use of 'db1' wavelet function, Convolution in the use of wkeep order the interception of data. Reconstruction of the original signal and signal more smaller error.)

msk的matlab调制与解调仿真，使用延时相干解调方式，包含差分编码与解码模块(modulation and demodulation of msk of Matlab simulation, delay Demodulation, including differential encoding and decoding modules)

this is the full search block matching agorithm algorithm for motion estimation

本课件重点讲述了层次分析法的要点，通过例题完全的解析了层次分析法中在系统建模与仿真中的解题思路!(The courseware focuses on the main points of the analytic hierarchy process, by example completely resolve the Analytic Hierarchy Process System Modeling and Simulation in solving ideas!)

详细且一目了然的RS编译码matlab仿真程序。 包括GF(Q)域的各种运算（每种运算一个函数功能文件），RS编码模块及译码模块。 期中译码模块又分为伴随式计算模块，错误位置多项式计算模块，错误位置计算模块，错误数值计算模块。 还包含了专门用于测试每个模块是否正确的testbache。完整，详细，正确(Detailed and clear RS codec matlab simulation program. Including the GF (Q) domain of a variety of computing (computing a function of each functional document), RS coding and decoding module module. During the decoding module is divided into modules with computing, error location polynomial calculation module, the error location calculation module, module numerical error. Also includes a special module for testing the validity of each testbache. Complete, detailed and correct)

小波域高斯混合模型与中值滤波的混合图像去噪研究(Gaussianmixturemodelinwaveletdomainmedianfilteringandhybridimagedenoising)

This program calculates the texture features of a given image based on the grey level co-occurences. Instead of creating a matrix of the co-occurences (GLCMs), this program implements

complex signal generator

说明：  Chau Yuen的酉空时码例程， 瑞利衰落信道下，采用4发1收，比较了不同信噪比下的BER和SER(Chau Yuen Unitary space-time code routines, Rayleigh fading channel, using 4-fat one collection, comparison of different signal to noise ratio of BER and SER)

adaboost代码，比较简单。但方便了解Adaboost算法的基本原理(The aim of the project is to provide a source of the meta-learning algorithm known as AdaBoost to improve the performance of the user-defined classifiers. )