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205-GHz (Al,In)N/GaN HEMTs.more than 15 years of development, AlGaN/GaN high-electron-mobility transistors (HEMTs) have become the most technologically mature form of GaNbased HEMTs. There is, however, growing evidence that the total strain (i.e., the lattice-mismatch and piezoelectric contributions) limits the reliability of conventional AlGaN/GaN HEMTs

说明：  这个程序是使用MATLAB对ofdm中的压缩扩张技术降低PAPR技术的仿真，程序仿了不同u值下的对PAPR的降低程度不同(that is a simulation of papr using matlab ,it is using u_law companding)

Elman神经网络：Elman网络是 J. L. Elman于1990年首先针对语音处理问题而提出来的, 它是一种典型的局部回归网络( global feed for ward l ocal recurrent)。Elman网络可以看作是一个具有局部记忆单元和局部反馈连接的前向神经网络。Elman网络具有与多层前向网络相似的多层结构。它的主要结构是前馈连接, 包括输入层、 隐含层、 输出层, 其连接权可以进行学习修正 反馈连接由一组“结构 ” 单元构成,用来记忆前一时刻的输出值, 其连接权值是固定的。在这种网络中, 除了普通的隐含层外, 还有一个特别的隐含层,称为关联层 (或联系单元层 ) 该层从隐含层接收反馈信号, 每一个隐含层节点都有一个与之对应的关联层节点连接。关联层的作用是通过联接记忆将上一个时刻的隐层状态连同当前时刻的网络输入一起作为隐层的输入, 相当于状态反馈。隐层的传递函数仍为某种非线性函数, 一般为 Sigmoid函数, 输出层为线性函数, 关联层也为线性函数。(Elman neural network: Elman JL Elman network is first proposed for speech processing problems in 1990. It is a typical local regression network (global feed for ward l ocal recurrent). Elman network can be seen as having a forward neural network of local memory unit and local feedback connections. Elman network has a multi-layer multilayer structure similar to the network. Its main structure is a feedforward connection, comprising an input layer, a hidden layer and output layer, which can be connected right learning correction feedback connected by a set of " structural" units, the output value of the memory for the previous time, which connection weights are fixed. In such a network, in addition to ordinary hidden layer, there is a special hidden layer, called an associative layer (or contact layer unit) this layer receives feedback signals the hidden layer, each hidden layer node has an associated layer node corresponding connection. The role of the associated layer is fo)

This code is related to the course Digital Communications. It reproduce the error probability as a function of the SNR per bit for 16-QAM. Enjoy it!

用MATLAB实现动态聚类或迭代自组织数据分析，最大信噪比的独立分量分析算法，小波包分析提取振动信号中的特征频率。( Using MATLAB dynamic clustering or iterative self-organizing data analysis, SNR largest independent component analysis algorithm, Wavelet packet analysis to extract vibration signal characteristic frequency.)

此程序是在假设已知波达角的情况下进行仿真验证的实验，零陷music波速成形。(This procedure is known in the hypothetical case of DOA conducted simulation experiments, velocity forming nulls music.)

可以实现多个方向波束跟踪，并且抑制干扰信号(Can implement multiple direction beam tracking, and suppress interference signals)

耦合影响格子序列仿真，随机性，平衡性，级多瓣分治混沌序列在cnma中的应用(Simulation of the impact of lattice coupling sequence, randomness, balance, class of chaotic sequence多瓣divided the application in cnma)

filter，本代码主要介绍filter的主要步骤，非常简单有很明了，非常适合阅读(Filter, the code describes the main steps of filter are very clear, very simple, very suitable for reading)

根据多行三列的实验数据（x,y,signal)作出contourf图。其中x,y为二位空间位置（或其他概念的二维），signal为在该位置的信号。此代码先将数据按位置不同求平均，再将signal按照其对应的x,y分配到二位矩阵内。最后作图。编这个代码的初衷是为了制作大脑hippocampus区域place cell 活动性的contour 图。(it s a code i made for plotting a contour graph of experimental data (x,y,signal). The data should be n*3 arrays which cannot be plot into contour directly. In fact, it can subplot 6*6 graphs or more, but speed might be slow..... especially, when you want more detailed graphs.)