yixuetuxiangchuli

贝叶斯分析，比较复杂的自回归分析。VAR模型，注意比AR要先进的多！(Bayesian estimation, prediction and impulse response analysis in VAR models using the Gibbs sampler.)

这是用matlab编写的一个kalman滤波器，数字信号实验维纳滤波，估计AR模型参数(using Matlab is prepared by a Kalman filter, digital signal experimental Wiener filtering, AR model parameters estimated)

本程序的性能已经达到较高水平，采用波束成形技术的BER计算，有详细的注释，可以得到很精确的幅值、频率、相位估计。( The performance of the program has reached a high level, By applying the beam forming technology of BER There are detailed notes, You can get a very accurate amplitude, frequency, phase estimation.)

Matlab code for Massive mimo simulation with MMSE channele estimation and Approximate message passing: a comparison

现今阵列应用中，宽带信号的处理越来越多。由同心圆阵组成的多圈圆形阵列在宽带信号处理上有更强的优势。和单圈均匀圆阵相比，同心多圈圆阵的嵌套设计阵列工作频率范围更宽，同时，灵活性增强。 (Nowadays array applications, the broadband signals in many more and more treatment. By the array composed of many concentric circular ring array of broadband signal processing at up there is more advantage. And single-lap compared to uniform circular array, circular array concentric circle many nested design frequency range of a broader array of work at the same time, enhance flexibility.)

matlab用户图形界面用法的一个小例子。用到了文本框、滚动条等控件，对刚开始学习matlab有一定的帮助。(matlab graphical user interface uses a small example. Used in the text boxes, scroll bars, and other controls, just started learning matlab have some help.)

通信系统中的信号调制与解调技术，对信号比特流进行8QAM信号调制与解调的matlab仿真。(Communication system signal modulation and demodulation techniques for signal simulation matlab 8QAM bitstream signal modulation and demodulation.)

利用matlab实现简单的数字信号处理的问题，有详细的源代码和分析(Using matlab to achieve a simple digital signal processing problems, detailed source code analysis)

QPSK modulation and again demodulation

说明：  假如数据中有N 个变量，而我们想抽取的样本的数量是M,那么在对数据进行抽样的时候，这种方法首先会把N个变量的设计空间均匀的划分开为M份，然后在每个划分好的区域中随机的抽取一点，最后，从这M个变量里，随机挑选之前选好的点，构成我们的样本(If there are n variables in the data, and the number of samples we want to extract is m, then when sampling the data, this method will first divide the design space of n variables into M parts evenly, and then randomly extract a point in each divided area. Finally, from the m variables, randomly select the previously selected points to form our sample)