matlab-self-taught-60-codes

海明码发送与接收程序 测试信道的可靠性 可单独设立监听端口(Hamming code to send and receive testing the reliability of channel can be set up to monitor a separate port)

consider the power and spectrum

说明：  近年来，DOA估计越来越被广泛注意，该内容用MUSIC实现DOA估计(In signal processing, pulse compression has a wide range of applications, the file is implemented with MATLAB)

对一段语音进行加窗处理，在matlab下查看经过加窗处理后的语音信号。(For a voice to add Windows processing, on matlab check after add window under process after the speech signal)

经典的模遗传算法的合集，是我在参加数学模型大赛时收集的，比较有用(classic mode GA universe, I was participating in the Mathematical Model Competition collected, more useful)

cdma 反向链路仿真 simulink( cdma 2000 simulink)

说明：  <<现代信号处理教程>>(胡广书版)书中配套的matlab源代码。(this is a matlab code of the book called modem signal processing.)

风电混沌序列时间延迟的计算，经证实简单有效(Wind the calculation of time delay chaotic sequence, proved to be simple and effective)

varias c++ de varias c++

说明：  遗传算法（Genetic Algorithm，GA）最早是由美国的 John holland于20世纪70年代提出,该算法是根据大自然中生物体进化规律而设计提出的。是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法。该算法通过数学的方式,利用计算机仿真运算,将问题的求解过程转换成类似生物进化中的染色体基因的交叉、变异等过程。在求解较为复杂的组合优化问题时,相对一些常规的优化算法,通常能够较快地获得较好的优化结果。遗传算法已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。(Genetic algorithm (GA) was first proposed by John Holland of the United States in the 1970s. It is designed and proposed according to the evolution law of organisms in nature. It is a computational model of biological evolution process simulating natural selection and genetic mechanism of Darwin's biological evolution theory. It is a method to search the optimal solution by simulating natural evolution process. The algorithm transforms the solving process of the problem into a process similar to the crossover and mutation of chromosome genes in biological evolution by means of mathematical method and computer simulation. When solving complex combinatorial optimization problems, compared with some conventional optimization algorithms, it usually can get better optimization results quickly. Genetic algorithm has been widely used in combinatorial optimization, machine learning, signal processing, adaptive control and artificial life.)