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Modeling Variable Annuities with MATLAB

matlab一些常用的命令和函数，还包括一些MATLABweb在线平台的资料(matlab some commonly used commands and functions, including some MATLABweb information online platform)

利用LMS算法来进行盲信号分离处理的程序(Using the LMS algorithm for blind signal separation processing procedures)

地基SAR基于两个点的形变检测，通过RD算法进行方位向压缩和距离向压缩，得到两幅图片，然后将这两幅图进行相位干涉得到形变量(SAR ground deformation detection based on two points, through RD algorithm azimuth compression and range compression to obtain two images, then these two figures to give shape variable phase interference)

自编的几个关于数字信号基本运算的程序，由此可以大大扩展信号运算的自由性与简洁性。(wrote several digital signal on the basic operations procedures, It can be greatly expanded signal operation and the freedom of simplicity.)

一个使用matlab语言编写的粒子群算例，对初学者很有用(a example of particle swarm optimization)

说明：  simulink工具箱的常见问题分析以及开发过程详解，初学适用(simulink toolbox of common problems and the development of Elaboration on the Course, for beginner)

基于L*A*B空间的色彩分割,可以直接运行，开发环境最好是MATLAB2009(COLOR CUT BASED ON LAB)

例4：在sinc(t)信号中叠加噪声，分析对应频谱 fs=100 采样频率,必须大于两倍基带信号最高频率 ts=1/fs 采样时间间隔 T=2 时间窗大小 ( x=x+0.1*randn(1,N) x=awgn(x,-10, measured ) figure plot(t,x) title( 时域信号图 ) xlabel( t /s ) y=fft(x,N) figure if mod(N,2)~=0 N=N-1 end f=linspace(0,fs/2,N/2) plot(f,abs(y(1:N/2))*2/N) title( 叠加噪声的sinc(t)信号频谱 ) xlabel( f /Hz ) figure y0=y(1:N/2) P=y0.*conj(y0)/N P=10*log10(P) plot(f,P) title( 功率谱 ) xlabel( f /Hz ) )

％File: c9_estimatepi.m ％有5个pi的估计，每一个都是基于500次重复随机试验，所得的pi的五个估计值用以下向量表示 ％pi的估计值=[3.0960 3.0720 2.9920 3.1600 3.0480] ％如果对5个结果进平均，则pi的估计值=3.0736,这样的结果等价于2500次的试验结果。( File: c9_estimatepi.m have 5 pi estimates are based on a randomized trial to repeat 500 times the income of the five estimated value of pi with the following vector, said the estimated value of pi = [3.0960 3.0720 2.9920 3.1600 3.0480] if the results into an average of 5, then the estimated value of pi = 3.0736, so the result is equivalent to 2500 times the test results.)