PCA_ORL

implementation batch method in pattern recognition

控制仿真很好的资料，包括滑膜变结构控制，希望对大家有用！(Control simulation of very good information, including the the synovial variable structure control, the hope that useful!)

adaptive median filter for image

使用BP神经网络训练数据并且作出预测，比较预测值与真实值的误差。(The use of BP neural network training data and make predictions, comparing predicted and actual values of error.)

说明：  BPSK的调制解调以及误码率等的matlab仿真(BPSK modulation and demodulation, and bit error rate of matlab simulation)

ch3=softt(h3,thr1 clear clc I=imread( lena512.bmp ) imshow(I) I=double(I) II=I+30*randn(size(I)) figure imshow(II,[]) [a1,h1,v1,d1]=dwt2(II, sym8 ) [a2,h2,v2,d2]=dwt2(a1, sym8 ) [a3,h3,v3,d3]=dwt2(a2, sym8 ) sigma=median(abs(d1(:)))/0.6745 x=3*sigma thr1=x*2^(-1) thr2=x*2^(-0.5) thr3=x 小波图像去噪( ch3=softt(h3,thr1 clear clc I=imread( lena512.bmp ) imshow(I) I=double(I) II=I+30*randn(size(I)) figure imshow(II,[]) [a1,h1,v1,d1]=dwt2(II, sym8 ) [a2,h2,v2,d2]=dwt2(a1, sym8 ) [a3,h3,v3,d3]=dwt2(a2, sym8 ) sigma=median(abs(d1(:)))/0.6745 x=3*sigma thr1=x*2^(-1) thr2=x*2^(-0.5) thr3=x )

在自适应信号的理想输入为有正弦信号。噪声输入也为一正弦信号。它们相互迭加，再经过LMS自适应算法，再比较它们的结果。(In an ideal adaptive signal has sinusoidal input signal. Noise input for a sinusoidal signal. Their mutual superposition, and then after LMS adaptive algorithm, and then compare their results.)

matlab的比较基础经典的教程，适合初学者的matlab从入门到精通(matlab basis for comparison classic tutorial for beginners from entry to the master)

说明：  4G通信技术综述，分析4G通信的优势及挑战，关键技术(Overview of 4G communications, analyzing the advantages and challenges of 4G communications, key technology)

详细功能图像的分析、包含内容说明分析的介绍 举例 以及图像说明(Detailed functional analysis of the image, including the content analysis of the introduction of example and image descriptions)