two_joint_workspace

continues analysis of discrete signal, not integer shifting of a discrete signal

说明：  该文件是基于simulink与matlab结合的DQPSK系统仿真，最终结果为信噪比--误码率曲线图。(The file is based on Simulink and MATLAB combined DQPSK system simulation, the final result is signal to noise ratio - bit error rate curve.)

详细的卷积编码与维特比译码算法。产生随机信号，对信号进行卷积编码，然后经过数值转换、格雷编码，QPSK调制，进入加噪信道，之后进行QPSK解调，格雷解码， 数制转换、 维特比译码得到接收端的信号。(Detailed convolutional coding and Viterbi decoding algorithm. Random signal, the signal convolution coding, and then through numeric conversion, Gray coding, QPSK modulation, plus noise into the channel, followed by QPSK demodulation, decoding Gray, number system conversion, Viterbi decoding to get the receiving end of the signal.)

Digital Communication Using Chaotic-Pulse-Position Modulation

BTL thay dai, dai so 2, giai tich, tich phan, matlab code, TS Le Xuan Dai

说明：  这些MATLAB的M文件分为两部分：程序清单A中收录了产生PPM-TH和PAM-DS这两个信号源的所有函数；程序清单B中收录了加性高斯白噪声（AWGN）信道建模，正交和非正交单脉冲PPM-TH接收机结构，以及反极性PAM-DS单脉冲接收机结构仿真所需的所有函数。(The MATLAB M-file is divided into two parts: A list of procedures in the collection of produce PPM-TH and PAM-DS two signal sources all functions Listing B, contains an additive white Gaussian noise (AWGN) channel construction mode, orthogonal and non-orthogonal single-pulse PPM-TH receiver structure, as well as anti-polarity PAM-DS receiver structure simulation of single-pulse all the necessary functions.)

说明：  压缩感知 根据匹配追踪算法自制的代码 直接调用即可，内有中文注释 ( Compressive sensing， the code is made from Match pursuit algorithm )

功能：该程序用于仿真时间同步算法双向不等时间同步方法与无时漂往返校时方法（RTT）。输入：节点间距离、钟漂。输出：两幅同步误差比对图。(Features: The program for the simulation of two-way time synchronization algorithm for time synchronization methods ranging from no time when the drift from school method (RTT). Input: the distance between nodes, clock drift. Output: two synchronization errors of the map.)

这里是matlab的ppt教程，希望对大家有所帮助(Ppt Here is the matlab tutorial, I hope all of you to help)

一般的esprit算法计算复杂度高，在计算子空间是算法比较烦，改一些矩阵算法可以减少其复杂度。(Esprit general algorithm of high computational complexity in the calculation of subspace algorithms trouble is, some matrix algorithm can be changed to reduce its complexity.)