getcore

说明：  拥有matlab用户界面的-卡尔曼滤波程序(Have a matlab user interface- Kalman filtering procedures)

The attached source code is the implemenation of acoustic echo canceller and noise reduction.

丰富的matlab函数库，可以作为参考资料(Matlab function library, can be used as reference material)

与matalbe有关的视屏教程和具体的实例的讲解(Matalbe the Screen with tutorials and examples to explain specific)

a=load( q.txt ) width=input( 请输入窗宽 ) step=input( 请输入步长 ) m=length(a) for i=1:floor((m-width)/step+1) s(i,1:width)=a(1,1+(i-1)*step:width+(i-1)*step) end b=max(max(s)) M=s./b Rs=input( 请输入本体集半径 ) nd=input( 请输入检测器数模 ) k=1 while k<=nd d{k}=rand(1,width) for i=1:floor((m-width)/step+1) if (norm(d{k}-s(i,:)))^2<Rs break end end k=k+1 end for j=1:nd for i=1:floor((m-width)/step+1) R(i)=(norm(d{j}-s(i,:)))^2(a = load (' q.txt' ) width = input (' Please enter the window width' ) step = input (' Enter step size' ) m = length (a) for i = 1: floor ((m-width)/step+1) s (i, 1: width) = a (1,1+ (i-1)* step: width+ (i-1)* step) end b = max (max (s)) M = s./b Rs = input (' Please enter the body set radius' ) nd = input (' Please enter the number of detector modules' ) k = 1 while k < = nd d {k} = rand (1, width) for i = 1: floor ((m-width)/step+1) if (norm (d {k}-s (i ,:)))^ 2 <Rs break end end k=k+1 end for j=1:nd for i=1:floor((m-width)/step+1) R(i)=(norm(d{j}-s(i,:)))^2)

基于独立成分分析的多声源分离程序包，涵盖了大部分独立成分分析的函数,经验证能够有效解决多声源分离问题。(Based on independent component analysis of multi-source separation package, covering most of the functions of independent component analysis.)

pll锁相环程序——matlab仿真，使用复数表示的正弦信号(Phase-locked loop matlab simulation program)

说明：  基于相位相关和L-M的图像拼接算法，感兴趣的可以参考一下。(Phase correlation and the LM-based image mosaic algorithm)

运用matlab语言编制的卡尔曼滤波程序。(matlab kalman)

变尺度随机共振代码，几年前用过的，喜欢的可以试试。(Stochastic resonance code, you can try a few years ago used.)