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rayleigh distribution multipath channel model

说明：  给定10帧点云，利用ICP的方法估计出机器人在这10帧的轨迹，并实现局部点云地图的生成(Given 10 frames of point clouds, the trajectory of the robot in these 10 frames is estimated by ICP method, and the local point cloud map is generated)

利用模拟退火算法改进的kmeans算法，可以实现分类也可以用来分割，matlab版本(Improved simulated annealing algorithm kmeans algorithm can also be used to classify segmentation, matlab version)

隐马尔科夫链的基本函数，对于一些图像识别问题有好多的作用(Hidden Markov chain' s basic function, for some pattern recognition problems have a lot of role)

说明：  一个双向LSTM程序 Long Short Term 网络—— 一般就叫做 LSTM ——是一种 RNN 特殊的类型，可以学习长期依赖信息。LSTM 由Hochreiter & Schmidhuber (1997)提出，并在近期被Alex Graves进行了改良和推广。在很多问题，LSTM 都取得相当巨大的成功，并得到了广泛的使用。 LSTM 通过刻意的设计来避免长期依赖问题。记住长期的信息在实践中是 LSTM 的默认行为，而非需要付出很大代价才能获得的能力！ 所有 RNN 都具有一种重复神经网络模块的链式的形式。在标准的 RNN 中，这个重复的模块只有一个非常简单的结构，例如一个 tanh 层。(A bidirectional LSTM program Long short term network, commonly known as LSTM, is a special type of RNN that can learn long-term dependent information. LSTM was proposed by Hochreiter & schmidhuber (1997) and recently improved and promoted by Alex graves. In many problems, LSTM has achieved great success and has been widely used. LSTM is designed to avoid long-term dependency. Remember that long-term information is the default behavior of LSTM in practice, not the ability to acquire it at a great cost! All RNNs have a chained form of repetitive neural network modules. In the standard RNN, this repetitive module has only a very simple structure, such as a tanh layer.)

ldcp编码解码源程序，用c语言写的，最后生成mex文件用于matlab使用 (ldcp codec source code, using c language, and finally generate mex file for matlab use)

关于OFDMA的介绍，初学者很容易理解。且有本人阅读时做下的一些笔记，愿对大家有用。(On OFDMA in the introduction, it is easy for beginners to understand. I read and have done at some of the notes, would like for all of us.)

说明：  Shi-78D隐写分析算法 ，是一种非常常用的隐写分析算法的代码。(Shi-78D Steganalysis)

线性最优状态调节器，一阶系统，Riccati方程的求解(Linear optimal state regulator, first-order system, Riccati equation)

matlab的经典书籍，百看不厌。 感兴趣的网友可以下载学习。(matlab classic book , never get tired . Interested users can download learning . )