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锁相环的工作模式：单载波为“1”、BPSK调制为“2”、QPSK调制为“3” 对其进行仿真 修改可用于高动态(The PLL operating modes: single-carrier is "1", and the BPSK modulation is "2", the QPSK modulation is "3." Its simulation modifications can be used for high dynamic)

说明：  matlab的函数库，里面详细的介绍了matlab各种函数的用法及参数说明，是学习matlab的必备宝典。(matlab function library, which describes in detail the use of matlab various functions and parameters that it is essential to learn matlab Collection.)

字符识别，较为入门的字符识别程序，基于MATLAB。适合入门(Character recognition, character recognition program is started, based on the MATLAB. Suitable for entry)

已知一个二维数据，y=f(x), 想使得这个数据绕y轴旋转而成为一个旋转对称的三维数据(A two-dimensional data is known, y=f (x), to make the data around the Y axis and become a rotationally symmetric 3D data)

录制自己的一段语音，时间控制在15秒到30秒左右；利用wavread函数对自己的语音进行采样，记住采样频率。 （1）画出原始语音信号的时域波形，而后以1秒为间隔，求出每秒数据的功率谱。 （2）根据语音信号特点，分别设计FIR及IIR滤波器，分别画出滤波器幅频和相频特性曲线。用设计的滤波器对信号滤波，画出滤波后时域波形。用sound函数回放语音信号。 （3）求出特征频段语音信号随时间变化的曲线（每间隔0.05秒求一次功率谱）。 (Record your own voice for some time (15 seconds to 30 seconds) use wavread function of the voice samples, remember the sampling frequency. (1) Draw the original speech signal in time domain waveform, and then to 1 second intervals, the data obtained power spectrum per second. (2) According to the voice signal characteristics, FIR and IIR filters were designed, namely to draw the amplitude and phase frequency characteristic curve. With the design of the filters on the signal filtering, to draw the filtered time-domain waveform. Playback with sound function of the speech signal. (3) Find the characteristic band speech signal curve over time (0.05 seconds intervals seeking a power spectrum.))

matlab如何与vb进行混合编程的案例，还包括部分计算方法的matlab实现(application example of matlab and VB)

本文件用于Matlab中使用高阶累积量的方法计算功率谱估计(This document is the use of Matlab for Higher Order Cumulants power spectrum estimation method)

matlab实现16QAM的调盒解调(matlab achieve 16QAM modulation demodulator box)

火箭升空动画，分为5个阶段，目前先上传一部分代码，后续继续(rock up to air flash)

依次阐述了非线性动力系统的建模，单自由度自治系统、单自由度非自治系统和多自由度系统的分析方法及动力学行为(Turn on the modeling of nonlinear dynamical systems, single degree of freedom autonomous system, single degree of freedom analysis methods and dynamic behavior of the non-autonomous system and multi-degree-of-freedom system)