xiaobotongyonghanshu

一个用PCA和LDA降维，并用knn分类的人脸识别例程(A dimension reduction using PCA and LDA, and face recognition with the knn classification routines)

Speech compression using Linear Predictive Coding. LPC is the oldest and the most basic of modern speech coders. Its a lossy scheme. Playback quality isn t preserved in the process but it can be used in low bit-rate systems.

对于OFDM系统在三种信道模型下进行了仿真，给出了误码率分析并绘图给出了结果(For OFDM system in the three channel model simulation under the given bit error rate analysis and mapping results are given)

元胞自动机模拟火灾，森林火灾模型，树燃烧状态的转变(Cellular automata simulated fire)

使用卡尔曼滤波器对物体的未来状态进行预测和估计。(Using the kalman filter to predict the station of the object.)

基于混沌的模拟退火算法，计算机的优化算法，是毕设的内容(Chaotic simulated annealing algorithm, the computer algorithm is complete contents of set)

The class for working with configurations of settings and INI-files

分形的练习一 ①Koch曲线 用复数的方法来迭代Koch曲线 clear i 防止i被重新赋值 A=[0 1] 初始A是连接（0，0）与（1，0）的线段 t=exp(i*pi/3) n=2 n是迭代次数 for j=0:n A=A/3 a=ones(1,2*4^j) A=[A (t*A+a/3) (A/t+(1/2+sqrt(3)/6*i)*a) A+2/3*a] end plot(real(A),imag(A)) axis([0 1 -0.1 0.8]) ②Sierpinski三角形 A=[0 1 0.5 0 0 1] 初始化A n=3 迭代次数 for i=1:n A=A/2 b=zeros(1,3^i) c=ones(1,3^i)/2 A=[A A+[c b] A+[c/2 c]] end for i=1:3^n patch(A(1,3*i-2:3*i),A(2,3*i-2:3*i), b ) patch填充函数 end (Fractal Exercise One The ① Koch curve Plural iteration Koch curve clear i to prevent i is reassigned A = [0 1] initial A is a connection (0,0) and (1,0) of the segments t = exp (i* pi/3) n = 2 n is the number of iterations for j = 0: n A = A/3 a = ones (1,2* 4 ^ j) A = [A (t* A+ a/3) (A/t+ (1/2+ sqrt (3)/6* i)* a) A+2/3* a] end plot (real (A), imag (A)) axis ([0 1-0.1 0.8])   ② Sierpinski triangle A = [0 1 0.5 0 0 1] initialized A n = 3 the number of iterations. for i = 1: n A = A/2 b = zeros (1,3 ^ i) c = ones (1,3 ^ i)/2 A = [A A+ [c b] A+ [c/2 c]] end for i = 1:3 ^ n patch (A (1,3* i-2: 3* i), A (2,3* i-2: 3* i), b ) patch filled function end)

This file is implementation of a algorithm include mixture of genetic algorithm and bbo

包括主成分分析、因子分析、贝叶斯分析，对信号进行频谱分析及滤波，是国外的成品模型。( Including principal component analysis, factor analysis, Bayesian analysis, The signal spectral analysis and filtering, Foreign model is finished.)