matlab_GPS

LDPC(Low-density-parity-check，低密度奇偶校验)码是一类具有稀疏校验矩阵的线性分组码，不仅有逼近Shannon限的良好性能，而且译码复杂度较低，结构灵活，是近年信道编码领域的研究热点(LDPC (Low-density-parity-check, low-density parity check) codes are a class of sparse check matrix of linear block codes, is not only good performance approaching Shannon limit, and the decoding complexity low, flexible structure , the field of channel coding in recent years the research focus)

很好的matlab教程，适合初学者用，很有帮助~(Matlab tutorials good for beginners to use, very helpful ~)

《MATLAB及在电子信息课程中的应用》一书中所有例题和习题的MATLAB源程序(MATLAB and electronic information in the application of the curriculum," a book of all the MATLAB examples and exercises source)

介绍matlab的腐蚀，膨胀，开运算，闭运算，细化，去噪等的指令，对于初学者非常有用。(Introduction matlab corrosion, expansion, opening operation and closing operation, refinement, noise and other instructions, very useful for beginners.)

matlab例程MATLAB 6.x版的内建数据类型（Built-in data type）就有5种以上，此外还有许多其他专门设计的类（Class），如符号类、内联函数类、控制工具包中的线性时不变模型类、神经网络类等。就程序设计而言，MATLAB 6.x版采用了面向对象编程技术。数据和编程的改变使用户能更简捷而自然地解决复杂的计算问题（如符号计算问题、多变量控制系统问题、神经网络问题）。本章内容根据MATLAB6.5编写，但绝大部分内容适用于其他MATLAB6.x版本。(Matlab routines MATLAB 6.x version of the built-in data types (Built-in da ta type) have more than five, in addition to many other specialized design category (Class). If symbol, which together function category, tool kits control the linear time-invariant model type, neural network type. On the design process, using MATLAB 6.x version of the object-oriented programming technology. Programming and data changes so that users can more simple and natural solution to the complex calculation (as symbolic computation, multivariable control systems, neural networks). According to the contents of this chapter MATLAB6.5 preparation, But most of what applies to other MATLAB6.x version.)

对谐波信号进行分析，获得音调和基频，来自音色工具箱(Harmonic signal analysis, the tone and the fundamental frequency from the tone toolbox)

Continuous Ant Colony Optimization

模型参考自适应系统的simulink文件(The simulink File of the model reference adaptive system)

将背景音乐（交响乐）中的摩斯电码找出并分离出来(morse_code_sound.wav is a mono (1-channel) 11,025 samples per sec, 16-bits per sample, WAV file. There is a morse code signal within the audio file, you should be able to hear it in the background, but it is not very audible (able to be heard). Write a Matlab program to analyze the wav file and determine the narrow range of frequencies occupied by the morse code sound. Then separate the morse code sound into a separate file and the music into a separate file. Write out the separated morse code and the separated music to separate wav files titled your_name_morse.wav and your_name_music.wav)

Save the image in several formats and calculate their mean square error