57871831template_matching

ofdm粗频偏估计程序，包含5个模块，基于PN序列的同步(ofdm coarse frequency offset estimation procedures, including the five modules)

LAWMLShrink图像去噪方法MATLAB程序(LAWMLShrink Image Denoising MATLAB program)

matlab编写的调整svm参数的程序，其中cross是主程序，另两个是自己编写的svm核函数，如果要用matlab自带的核函数就把-t的值改成2即可。Ytrain是标记矩阵，Xtrain是特征矩阵，都由用户自己导入。可利用k倍交叉验证来选择最优的c参数。k可自行更改。(svm matlab prepared to adjust the parameters of the program, which cross the main program, and the other two are themselves prepared svm kernel function, if you use the value of the kernel function matlab own put-t can be changed to 2. Ytrain is labeled matrix, Xtrain is characteristic matrix, imported by the users themselves. K-fold cross-validation can be used to select the optimal c parameter. k can make changes.)

matlab code for image processing and segmentation

说明：  通过对独立分量分析算法的研究，介绍了该算法的基本模型及目前应用最广泛的快速定点ICA算法的数学原理．通过仿真试验结果表明，用该算法对随机混合的3幅图像进行盲分离，取得了理想的效果．(By independent component analysis algorithm, introduced the algorithm for the basic model and is currently the most widely used fast fixed-point ICA algorithm of mathematical principles. Through the simulation test results show that the algorithm to a random mixture of three images in blind source separation, and achieved the desired results.)

利用模式理论，对给定几何尺寸以及折射率分布的光纤进行模式求解与绘图，该程序给出LP01模的求解与绘图。(the LP01 mode of the fiber. )

一种现代智能优化算法 ，利用群体智能，全局搜索能力强(A modern intelligent optimization algorithms, the use of swarm intelligence, global search ability)

NMF聚类算法matlab实现，仅作为参考，有数据，可以直接运行( NMF clustering algorithm matlab realize, only as a reference, the data can be directly run)

3GPP标准Turbo码编码译码仿真Matlab6.5及VC6.0源代码，并包含Turbo码编码译码原理的介绍文档。(3GPP standard Turbo coding and decoding simulation VC6.0 Matalab 6.5 source code , and includes Turbo Encoder Decoder description of the principle of documentation.)

说明：  matlab 一维二维小波分析处理，并比较不同小波去噪方法的去噪效果，指标为SNR和MSE(Matlab one dimensional two dimensional wavelet analysis processing.The denoising effects of different wavelet denoising methods are compared, and the indicators are SNR and MSE)