A1.tar

雷达系统仿真，采用相位编码脉内线性调频混合调制信号。该雷达具有数字化正交解调、脉冲压缩处理、固定目标对消、动目标检测（MTD）、和恒虚警（CFAR）处理等功能(Radar simulation system，using the LFM and barker code mixed modulated signal。Main function include：digital orthogonal demodulationfixed, Pulse compression，target cancellation, moving object detection (MTD), and the constant false-alarm (CFAR) processing etc)

用七元线形天线阵（ULA） 已知：信号中心波长为2,天线阵元的间距为1米,快拍数为2000，空中有四个 源信号,假设它们的频率：0.015, 0.05, 0.02, 0.035 四个源信号的方向分别为：pi/4 pi/3 pi/6 3pi/4 求： 1）在不加入噪声的情况下,画出传统波束形成法、Bartlett波束 形成法、Capon波束形成法的空间谱图； 2）在加入高斯白噪声的情况下,假设信噪比为10dB，画出传统波束 形成法、Bartlett波束形成法、Capon波束形成法的空间谱图。(7-element linear antenna array (ULA) Known: the signal center wavelength is 2, the antenna element spacing of 1 m, the number of snapshots for 2000, the air there are four Source signal, assuming that their frequency: 0.015, 0.05, 0.02, 0.035 The direction of the four source signals: pi/4 pi/3 pi/6 3pi/4 Requirements: 1) not to join the noise, to draw the traditional beam-forming method, Bartlett, beam Formation method, Capon beamforming method of the space spectrum 2) by adding Gaussian white noise, assuming that the SNR is 10dB, to draw the traditional beam Formation method, Bartlett, beamforming, Capon beamforming method of the space spectrum.)

matlab code for finding mean variance auto correlation and psd

DOA估计与阵元数关系的MUSIC程序，可完成MATLAB的波形仿真。(DOA estimation the the MUSIC program relationship with the number of array elements, to be completed by MATLAB waveform simulation.)

自己编写的多项式拟合的例子程序，matlab多项式，。(I have written an example of polynomial fitting procedure, matlab polynomial.)

一个较好的无刷直流电动的MATLAB的仿真模块，有图有真相，祝各位好运。(A better brushless DC electric MATLAB simulation module, there are pictures and the truth, and I wish you good luck.)

说明：  E5去白噪声、高斯白噪声分析的源程序，用来处理做分析前的数据(E5 to white noise, Gaussian white noise analysis of the source)

M_sequence Generator

三电平VSC仿真，使用与初学多电平的人员，MATLAB仿真可运行，(MATLAB three level simulink)

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.)