6D

结合cmac 的pid控制原码 可仿真实现 结果有误差曲线 跟踪曲线 参数整定曲线等(Combination of CMAC)

练习1：查找内存错误 练习2：阅读书籍高质量ç 编程指南.PDF林锐（林锐）P95，回答问题4。 练习3：阅读代码sizeof.rar。不运行它，它的分析和写入输出。(Practice 1: Finding Memory Bugs Practice 2: Read book 高质量C编程指南.pdf  by Lin, Rui(林锐) P95, answer question 4. Practice 3: Read the code in sizeof.rar. Without running it, analysis it and write the output.)

This code describes the blind channel estimation problem for the estimation of different estimation schmes.

说明：  归一化梯度 matlab编写的一种算法，以及处理过程(Normalized gradient)

基于bregman算法在一维、二维、三维信号处理中的应用matlab工具箱(This toolbox provides the source code associated with the Bregman Cookbook Doc: - BregmanCookbook.pdf In 1D: -L1_SplitBregmanIteration.m : performs the recovery of a sparse signal affected by a known linear operator In 2D: -AddCurveletArray.m : sum the curvelet coefficients of two decomposition structures -AddFrameletArray.m : sum the framelet coefficients of two decomposition structures -ATV_NB_Deconvolution.m : performs the Nonblind Anisotropic Total Variation Deconvolution -ATV_ROF.m : performs the Anisotropic Total Variation Denoising -ITV_ROF.m : performs the Isotropic Total Variation Denoising -Curvelet_NB_Deconvolution.m : performs the Nonblind Deconvolution based on Curvelet sparsity -Framelet_NB_Deconvolution.m : performs the Nonblind Deconvolution based on Framelet sparsity (Analysis approach) -Framelet_NB_Deconvolution2.m : performs the Nonblind Deconvolution based on Framelet sparsity (Synthesis approach) -ShrinkCurvelet.m : performs the shrinkage of cu)

Antenna and EM Modeling with MATLAB

使用程序实现mse函数的三维设计实现，可以表现出不同的最小均方误差的各种情况(MSE realize the use of procedures designed to achieve three-dimensional function, can be expressed in different MMSE various situations)

local histogram maching

可以拟合两点之间的偏差，只需要给出函数相应的数据(The deviation between two points can be fitted, only the corresponding data are given functions)

matlab数学建模中的15个模型的算法讲解与举例，包括灰色预测、灰色关联分析、主成分分析法、模糊聚类分析、随机模拟、多元回归模型、正交试验设计、图论、目标规划模型、马尔可夫预测方法、时间序列分析、模糊综合评价模型、层次分析模型、模糊数学方法、模拟退火算法。(15 model matlab mathematical modeling method to explain with examples, including the gray prediction, gray correlation analysis, principal component analysis, fuzzy clustering analysis, stochastic simulation, a multiple regression model, orthogonal design, graph theory, goal programmingmodel, Markov forecasting methods, time series analysis, fuzzy comprehensive evaluation model, analytic hierarchy model, fuzzy mathematical methods, simulated annealing algorithm.)