MC_QPSKModDemod_ShapeAndMatch

这是用SIMULINK的S-FUNCTION方式编写的系统仿真代码，系统是基于4G网络的核心技术空时分组编码的MIMO-OFDM通信系统的，涉及到空间分集、时间分集和频率分集的有机结合，包括QPSK调制解调、IFFT调制、控制编解码、基于训练符号的信道估计等通信模块。包括main_STBC_MIMO_OFDM和training_symbol两个M文件和一个DOC文件，对各部分的都有详细的代码和注释。(It is used SIMULINK the S-FUNCTION approach to the preparation of the system simulation code, the system is based on the 4G network s core technology space-time block coded MIMO-OFDM communication system, involving spatial diversity, time diversity and frequency diversity of the organic combination, including QPSK modulation and demodulation, IFFT modulation, control of encoding and decoding, symbol-based channel estimation training and other communication module. Including main_STBC_MIMO_OFDM and training_symbol two M file and a DOC file, have detailed the various parts of the code and comments. )

Simulink通信系统建模一书中的MIMO通信系统仿真MATLAB源程序，包括word文档介绍，是非常好的通信系统仿真的学习参考资料(The book Communication Systems Simulink modeling the MIMO communication system simulation MATLAB source code, including word document describes, is a very good communication system simulation study reference)

读取计算机上的图片，图片格式的转换，并对二值化的图像进行radon变换，变换角度分别是0°、25°(Read the pictures on your computer, convert image format, and binarized image radon transform, transform angle are 0,25)

一些matlab学习中间比较常用的课后练习的源代码程序。(Some among the more common learning matlab exercises the source code program.)

system identification

讲述了现在机械故障诊断中用到的常用时频分析方法，如短时fft 魏格纳维尔分布 小波变换 HHT等，里面含有例子和详细说明，对初学者帮助很大。(Tells the now commonly used in mechanical fault diagnosis frequency analysis methods, such as short-time wavelet transform fft Wigner distribution HHT Louisville, etc., which contains examples and detailed instructions, very helpful for beginners.)

matlab编写的熵权代码，很实用的东西(Entropy matlab code written, very practical things)

CRS 去噪代码，可以在matlab上运行，是从别的地方找来的。测试或可以用(CRS denoising code can be run in matlab, is recruited from elsewhere. Test or you can use)

Computational Building Physics and Systems 7

通过并行压缩进行二维信号压缩，提出了一种利用并行压缩传感技术对二维信号进行压缩的新方案。根据这个原理，译码器的重新构造可以并行进行。通过对二维信号进行某些排列，可以确保所有列具有大致相同的密度级别，并且可以使用相同的测量矩阵进行采样。这样可以避免二维信号的矢量化，从而大大减小测量矩阵的尺寸。我们证明，如果排列良好，重建均方误差的上限会更紧。为了说明这一方案，我们将其应用于视频压缩并使用不同帧的排列有两种：参考帧的基于Z字形扫描的排列和非参考帧的基于块测试的排列。仿真结果表明，在相同的压缩比下，峰值信噪比比比在无置换情况下可提高3-7db左右。(we propose a new scheme to compress 2D signals using parallel compressed sensing. According to this seheme, the reeonstruction at the decoder can be performed in parallel. By performing certain permutation on a 2D signal, all columns are insured to have approximately the same density level and can be sampled using the same measurement matrix. In this way, vectorization of a 2D signal can be avoided, and thus the size of the measurement matrix can be dramatically reduced. We prove that with a good permutation, we can have a tighter upper bound on reconstruction mean square error. To illustrate this scheme, we apply it to video compression and use two kinds of permutations for different frames: the zigzag-scanbased permutation for reference frames and the block-test-based permutation for non-reference frames. Simulation results show that under the same compression ratio, the peak signal-to-noise ratio can be improved by approximately 3-7 dB compared to the case without permutation.)