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Matlab 实例-编写M脚本文件，涉及比较深层的 MATLAB 内容：脚本；函数（一般函数、内联函数、子函数、私用函数、方法函数）；程序调试和剖析；数据结构（类、对象）；重载和继承；面向对象编程。本章配备了许多精心设计的算例。这些算例是完整的，可直接演练的。读者通过这些算例，将真切感受到抽象概念的内涵、各指令间的协调，将从感知上领悟到面向对象编程的优越和至关要领。(Matlab Examples- the preparation of M script file, involving comparison MATLAB deeper content: script function (general function, inline function, Functions, Private Functions, methods, functions) program debugging and analysis data structure (class, object) Overloading and inheritance object-oriented programming. This chapter with a number of carefully designed examples. These examples are complete, can directly exercise. Through these examples the reader will really feel the meaning of abstract concepts, the coordination between commands from realizing that the perception of object-oriented programming and to the superior customs essentials.)

实现各种图的网络结构的实现方法，是学习传感器网络的很好的软件(Network structure to achieve a variety of graph realization method is good to learn a software sensor networks)

(美)Pratap Misra，(美)Per Enge著 罗鸣，曹冲，肖雄兵译 《全球定位系统 Global positioning system 信号、测量与性能》随书光盘内容（包括MATLAB程序）((United States) Pratap Misra (United States) Per Enge Luo Ming, Cao Chong, Xiao Xiongbing translation of " Global Positioning System Global positioning system signals, measurement and performance" CD with the book all content (including MATLAB program))

一个使用setappdata，getappdata的matlab中guide参数传递的例子(A setappdata, getappdata matlab guide parameter passing example)

这是一个Alamouti空时码的仿真，包含2发1收或2发2收。(This is an Alamouti space-time code simulation, including two made an entry or two 2 admission.)

利用遗传算法优化PID参数，自动搜索最有 的PID参数(Using genetic algorithm to optimize PID parameters and automatically search the most PID parameters)

This code is useful for two paths rayleigh signals

压缩感知 重构算法集合 包含：CoSaMP,GBP,IHT,IRLS,MP,OMP,SP(Reconstruction algorithms for sparse Representation of Compressed Sensing)

振动信号的功率谱的相关程序，对于信号处理是很有用的(Power spectrum of the relevant procedures)

this algorithm simulates natural behavior of weeds in colonizing and finding suitable place for reproduction.IWO differs from other evolutionary algorithms in the way of reproduction,spatial dispersal and competitive exclusion