LTE_detect_OLSM

Kalman滤波，能快速收敛，对学习Kalman 滤波的朋友会很有用(Kalman filtering, fast convergence, a friend of the Kalman filter to learn useful)

说明：  距离波门拖引干扰模型，拖引过程实时显示，以GIF图片保存(Distance gate towing interference model, real-time display of towing process, saving with GIF picture)

说明：  Simulation for comparison of DVR and Other compensating devices

Program to look all the paths from N sources each other.

反应扩散方程中布鲁塞尔子的模拟~反应扩散方程中布鲁塞尔子的模拟~(Reaction-diffusion equations in Brussels analog sub ~ reaction-diffusion equations in the sub-analog ~ Brussels)

Daniel P. Palomar 2010的新作，凸优化在信号处理及通信中的应用。对于研究领域为通信理论及信号处理的学生而言，我强力推荐本书。(Daniel P. Palomar s new book published in 2010, 《convex optimization in signal processing and communications》. For the students in the areas of communication theory and signal processing, I strongly recommend this book.)

mimosimulation，ofdmsimulation(mimosimulation, ofdmsimulation)

platEMO是Ye Tian等学者写的一款基于MATLAB的多目标优化工具，为新入门的同学或者开发者提供了很大的便利，其今年已经发布到PlatEMO 2.0版本了。这款工具主要具有以下的几个特点： 1.完全由MATLAB开发，不需要任何其它库。 2.包括现有的90个流行的MOEAs，包括遗传算法、差分进化、粒子群优化、模因算法、分布估计算法和基于代理模型的算法。其中大多数是2010年以后在顶级期刊上发表的代表性算法。 3.用户可以显示各种图形，包括结果的pareto front，真实的pareto front等等。 4.强大友好的GUI，可以不用编辑任何代码。 5.可以直接生成Excel或者LaTex。(PlaEMO is a multi-objective optimization tool based on MATLAB written by Ye Tian and other scholars. It is a great convenience for beginners or developers. It has been released to PlatEMO version 2.0 this year. This tool has the following characteristics: 1. Developed entirely by MATLAB without any other libraries. 2. Including 90 popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, meme algorithm, distribution estimation algorithm and proxy model-based algorithm. Most of them are representative algorithms published in top journals after 2010. 3. Users can display various graphics, including Pareto front, real Pareto front and so on. 4. Powerful and friendly GUI, you can edit no code. 5. Excel or LaTex can be generated directly.)

滑模变结构控制的MATLAB程序一书的程序，希望对大家有用！(Sliding mode control process of the book MATLAB program, we want to be useful!)

Tucker, PARAFAC, GRAM, RAFA and misc. 2nd order models with a test data set (old version now covered by the N-way Toolbox)(Tucker, B6, GRAM, RAFA and misc. 2nd order models with a test's data et (old version now covered by the N-way Toolbox ))