circling_sound

cdma system simluation

function [bestsole,bestpop]=ga_scomplex(num,bounds,ps,pc,pm,b,dtc) % GA＿scomple是基于浮点编码的单纯形遗传算法主程序 % num定义种群数量 %　bounds定义参数取值范围，格式为[Var1min,Var1max;Var2min,Var2max;…….]; %ps选择概率 %pc交叉概率 %pm变异概率 %b　变异程度系数 %dtc　迭代次数 % $Date: 2005/5/25 $(funzione [bestsole,bestpop]=ga _scomplex (num,limites,ps,pc,pm,b,dc) % GA 655343;scomple;;;;;; % num % limits23450;[Var1min,Var1max;Var2min,Var22min;;;;;]; %ps %pc %pm %b _ %dtc _ % $Data: 2005 /5 /25 $)

说明：  matlab程序绘制世界地图，这是一个与etopo类似的地形绘制包，很清晰(Matlab program to map the world, this is a similar to etopo terrain mapping package, very clear)

1.设计自适应信号分离器，用以从白噪声中提取周期信号。其中选取正弦信号s=sin(2*pi*t/10)为周期信号，宽带噪声信号为高斯白噪声，设置参考通道延迟为50。 2.宽带信号中的窄带干扰抑制实际上是自适应信号分离的一种应用，借助自适应信号分离器可以方便的实现窄带干扰的对消。(1. Design of adaptive signal separator, used to extract from the white noise periodic signal. The extraction of sinusoidal signals s = sin (2* pi* t/10) for periodic signals, broadband noise signal is Gaussian white noise, set the reference channel delay of 50. 2. Wideband signals in the narrow-band interference suppression is actually an application of adaptive signal separation, using adaptive signal separator can be easily achieved narrowband interference cancellation.)

数值分析中的插值与拟合，有详细的讲解和配套matlab源代码(Numerical analysis of interpolation and fitting, detailed explanations and supporting source code matlab)

Turbo码编码译码器的研究及其MATLAB实现.(TUrbo)

Minimum shift keying modulation

信号源的emd分解，得到imf分量，以及imf分量的时频图。(The signal source EMD decomposition, the IMF component, as well as the imf component time-frequency diagram.)

观察高次插值多项式的龙格现象： 给定函数f(x)=1/(1+25x^2)(-1<x<1).取等距节点，构造牛顿插值多项式N5（x）和N10（x）及三次样条插值函数S10（x）。分别将三种插值多项式与f（x）的曲线画在同一坐标系上进行比较(Observation of high order polynomial interpolation Runge phenomenon: the given function f (x) = 1/(1+25x ^ 2) (- 1 <x<1).取等距节点，构造牛顿插值多项式N5（x）和N10（x）及三次样条插值函数S10（x）。分别将三种插值多项式与f（x）的曲线画在同一坐标系上进行比较)

马氏距离是一种有效地计算两个样本集之间相似度的算法（数据之间协方差距离），与欧式距离相比，它考虑了各种特征之间的联系。本实验旨在通过给出的样本数据，设计一个最小马氏距离分类器并对测试点进行分类，然后将其与最小欧式距离分类器进行比较，实验得出当协方差矩阵为单位阵时，最小马氏距离分类器将与最小欧式距离分类器等价。本实验还根据实验样本设计贝叶斯分类器进行分类，并与最小马氏距离分类器进行比较，比较两种分类器的分类效果。(Markov distance is an effective method to compute the similarity between the two samples (data covariance distance), compared with the Euclidean distance, which takes into account the link between different characteristics. This experiment aimed at through the given sample data, design a minimum Mahalanobis distance classifier and classify the test points, and then compare it with the minimum Euclidean distance classifier. Experimental results showed that when the covariance matrix is a unit matrix, minimum Mahalanobis distance classifier with the minimum Euclidean distance classifier equivalent.In this experiment, according to the experimental design of the Bias classifier, and compared with the minimum distance classifier, the classification results of the two classifiers are compared.)