整理好的主动学习和半监督学习的多项算法例程代码

说明：  介绍LTE系统的经典书籍，有兴趣学习LTE系统的可以看看(LTE system introduced classic books, are interested in learning the system can look at LTE)

For speckle reduction .

应用matlab求解线性随机微分方程dx(t)=sin(x(t))+sigma*dB(t)的输出结果。(generates outcomes of solutions of the SDE dx(t)=sin(x(t))+sigma*dB(t))

clear all; omega=1000;sigma=20;M=3;c=-3;d=8; Fs=500;T=1.024; t=0:1/Fs:T-1/Fs; L=length(t); signal=sin(omega*t); noise=zeros(1,L); t1=T/2:1/Fs:T-1/Fs; L1=length(t1); w=0.1*randn(1,L1); noise(L-L1+1:L)=w; x=signal+noise; figure(1); subplot(411);plot(t,x); X=fft(x,L); for s=1:M     omega=c+d*s;     for n=1:L         psi(n)=exp(-(n-s*omega)^2/(4*s*omega)^2);     end     WTx(s,:)=((pi/s)^0.5/sigma)*ifft(X.*psi); end subplot(412);plot(t,abs(WTx(1,:)));                %输出尺度为s=1 subplot(413);plot(t,abs(WTx(2,:)));                %输出尺度为s=2  subplot(414);plot(t,abs(WTx(3,:)));                %输出尺度为s=3

MIMO单播系统  考虑一个窄带平坦衰落的MIMO单播系统，发送端配置N根天线，接收端配置M根天线，则该系统的信号模型可以写成如下形式：其中x=Fs,y分别是发送信号和接收信号，发送信号x是功率归一化的，即满足，F是预编码矩阵，s是需要发送的数据矢量，是信道矩阵，n是加性高斯白噪声。推导得信道容量为：                      其中                                 i=1,…,n,        的取值满足功率约束条件               。

to help in computer vision ,pattern recognition and machine learning research for grad students in image analysis and computer science works of masters and doctorate

MATLAB系统仿真验证与工程应用研讨会会议资料,具有较高的参考价值(MATLAB system simulation and data engineering workshop meeting, with a high reference value)

配电网重构，蚁群算法，非常好，非常适用，可以直接用(Distribution network reconfiguration, ant colony algorithm)

基于最佳维纳滤波器的盲解卷积算法，给定信号为任意类型子波，期望输出可以有五类选择 （类型1：零延迟尖脉冲；类型2：任一延迟尖脉冲； 类型3：时间提前了的输入序列；类型4：零相位子波；类型5：任意期望波形。）(Blind deconvolution algorithm based on Best Wiener Filter (Blind Deconvolution) has five types of desired output (type 1: zero-delay spike; type 2: any delay spike; type 3: time-advanced input sequence; type 4: zero-phase wavelet; type 5: arbitrary desired waveform).)

说明：  自适应控制算法的另一个Simulink模型，可运行，是无模型参考控制算法的一个应用实例，供共同学习和交流(Adaptive control algorithm to another Simulink model to run, there is no model reference control algorithm of an application example for the common learning and exchange)