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matlab自学的六十多个简单易学的小程序，学习完这六十多个程序之后，你的matlab水平将得到很大的提高！(matlab for learning by yourself!matlab for learning by yourself!matlab for learning by yourself!matlab for learning by yourself!)

music算法的测试程序，包括不同的波长信号，不同采样点数，不同的阵列形式(music algorithm testing procedures, including different wavelengths, different sampling points, a different form of an array)

微网联网模式下pq控制仿真，供大家一起参考学习。(Pq control simulation the micro mesh networking mode, the reference for everyone to learn.)

CSTR系统过程控制问题，内涵子函数调用程序，可以快速了解MPC在过程控制中的应用(CSTR process control problem)

Manage and Dock Figures into Group

附件中是国外测速雷达系统仿真的matlab程序，其中对雷达系统的仿真讲的比较透彻。(Annex is abroad matlab speed radar system simulation program, in which the radar system, a thorough comparison of the simulation stresses.)

电路 信号系统仿真的源码 基于multisim10.0(Signal System Simulation multisim10.0 based on the source)

单极性归零码的波形图及功率谱 一般信道,无噪声(Unipolar NRZ waveform of the power spectrum and the general channel, the noise-free)

matlab 软件帮助文档是中文的学习该软件必备文档 初学者适用(matlab software help documentation is an essential document for beginners of Chinese to learn the software applicable)

圆卷积与线卷积在FIR中的实现，通过程序还开深刻理解两者间的差别和各自优劣。 1.圆卷积用在被截出的某段数据中，此时，长度应该定为和输入数据长度一致（一般输入数据大于hn的数），这时圆卷积结果相当于某段被截断出来的数据以非截断的方式经过滤波而得出的结果；线卷积用在各自独立的，离散的数据中，若截断数据也用线性卷积来计算，那么就相当与这部分数据是与源数据是独立的， 得出的结果时域两端会变长，但频谱基本上一样的。差别可以想象。 2.注意圆卷积最开始的输入数据的次序，构造矩阵时要注意。(Circular convolution with the line convolution in the FIR implementation, the program also opened a deep understanding of the difference between the two and their respective pros and cons. A circular convolution with cut out a certain period of data At this point, the length should be set for the same length as the input data (typically input data greater than hn the number), when the circular convolution is equivalent to a certain the results of the truncated data to the non-truncated filtered line convolution with a separate, discrete data, truncated data with a linear convolution calculation, then the equivalent of this part of the data is independent of the source data, the results of both ends of the time domain becomes long, but the spectrum is basically the same. The difference can imagine. Note that the order of the circular convolution of the input data to construct matrix.)