poisson

自适应噪声对消源程序，LMS算法自适应滤波器仿真。(Adaptive noise cancellation source, LMS adaptive filter algorithm simulation。)

Modeling mama barfi tisko Simulink

this code implemente a blind watermarking

本书包括MATLAB 7.0语言基础、基本应用、高级应用三部分。语言基础包括语言入门、程序设计基 础、矩阵线性代数算法实现；基本应用包括数据处理、数值计算、符号运算、图形处理；高级应用包括图形 用户界面编程、工具箱使用、模型使用、外部接口等。(This book includes MATLAB 7.0 language-based, basic applications, advanced applications of three parts. Introduction to basic language, including language, program design, the matrix linear algebra algorithms basic applications, including data processing, numerical computing, symbolic computation, graphics processing advanced applications, including graphical user interface programming, tool use, the model used, the external interface .)

使用MATLAB语言编写的有限元程序，是对[Programming_the_Finite_Element】中Fortran语言的MATLAB语言重写(Use MATLAB language finite element program is [Programming_the_Finite_Element MATLAB language] in Fortran language rewrite)

基于MATLAB的bpsk调制与解调的simulink仿真(bpsk modulation and demodulation based on matlab)

说明：  gps卫星位置预报，MATLAB编写，有动画界面(gps satellite position prediction, MATLAB prepared)

用matlab编写的龙曲线源程序，可以供大家参考(prepared using Matlab curve source of the Dragon, for your reference)

书中通过大量实例，介绍了如何利用遗传算法工具箱函数编写matlab程序，解决实际问题(Through a large number of examples in the book, introduces how to use genetic algorithm toolbox function. Write the matlab program to solve the actual problem )

七单元天线阵MUSIC DOA估计： d=1 ， 天线阵元的间距； lma=2， 信号中心波长； 四输入信号； A=[A1,A2,A3,A4]， 得出A矩； 四信号的频率d=[1.3*cos(v1*n) 1*sin(v2*n) 1*sin(v3*n) 1*sin(v4*n)] 构造输入信号矢量 U=A*d 总的输入信号 总输入信号的协方差矩阵 [s,h]=eig(c) 求协方差的特征矢量及特征值 取出与零特征值对应的特征矢量 求协方差矩阵的逆矩阵 应用Music法估计输出 绘出各波达方向图(Seven-element antenna array MUSIC DOA estimates: d = 1, Antenna Array pitch LMA = 2 signal center wavelength four input signals A = [A1, A2, A3, and A4], drawn A moment tetra-frequency of the signal D = [1.3* cos (V1* n) 1* ⁢ sin (v2* n) 1* sin (v3* n) 1* sin (V4* n)] constructed input signal vector U = A* D of the total input signal of the total input signal covariance matrix [S] = EIG (c) seeking covariance feature vector and the feature value removing and corresponding to the zero eigenvalues ​ ​ characterized vector seeking covariance matrix inverse matrix Applications Music estimate output plotted DOA Figure)