HausdorffDist

mat lab random walk code

学习ekf的一个源码，对初学者非常有用，随便下载并交流(Extended Kalman Filter Demo )

说明：  harris 角点检测的完整matlab程序 可直接运行(harris corner detection of the complete program can be run matlab)

由于matlab具有强大的矩阵运算优势，运用matlab计算平面梁的有限元方法(As a powerful matrix calculation matlab edge calculated using matlab finite element method for plane beam)

说明：  可转债定价模型，matlab编写，根据中国国情，考虑到修正条款(convertable bond)

单纯形算法的所有源程序，并举例两个函数说明，对函数用单纯形算法进行分析，寻找最优解。(Simplex algorithm of all source code, and that two functions, for example, use of function analysis of the simplex algorithm to find the optimal solution.)

在程序中用一般的MUSIC方法估计了信号的频谱，从两图中可看出在信号各频率处，频谱的峰值较大，故能明显的与噪声相区别，可在一定程度上避免在信号幅度较小时信号被噪声淹没的情况。(MUSIC method general procedures used to estimate the spectrum of the signal, it can be seen from the two graphs in the signal at each frequency of the spectrum peak larger, and it could be significantly distinguished from noise in the signal can be avoided to some extent a lesser extent, the signal is noise submerged.)

利用matlab实现了人脸检测的功能，主要是利用人脸颜色特征向量。(Matlab face detection function, face color feature vector.)

secant method by davo

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.