Homework1

简易的滤波器，毕业设计用的。希望对大家有用(Filter for matlab.very easy to learn )

SIFT特征提取算法的matlab实现，使用matlab和c的混合编程(SIFT feature extraction algorithm matlab realize, the use of matlab and c mixed programming)

用matlab编写的人脸检测程，效果非常高，附有文章以理解。(Matlab prepared with face detection process, the effect is very high, in order to understand the article attached.)

PLSAMA MATERIAL PROGRAME

使用FIR方法设计的滤波器，通过验证，可以使用。(FIR filter designed to use, validated, you can use.)

Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which is promising in exposing the more complicated correlation between original high-dimensional features. In this paper, we first talk about the basic ideas of PCA and kernel PCA, and then focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied to improve traditional ASMs. Then we show some experiment results to compare the performance of kernel PCA and traditional PCA for pattern classification. We also implement the kernel PCA-based ASMs, and use it to construct human face models.

图像处理第七章，matlab 书籍的源程序，图像处理(image processing program in matlab)

ofdm channel using and measure of PSNR

The code assembles various member stiffness matrices of a Q-4 element

正交频分复用光纤通信系统信噪比理论值计算(Orthogonal frequency division multiplexing with a theoretical value of the optical fiber communication system signal-to-noise ratio calculated)