chap_02

principal component analysis (PCA ) is a well known approach for dimensionality reduction of the feature space. It has been successfully applied in face recognition. The main idea is to decompose face images into a small set of feature images called eigenfaces, which can be considered as points in a linear subspace called “face space” or “eigenspace”

code for sobel edge detection

李雅普诺夫分析为线性系统的分析做出理论铺垫(Lyapunov theory)

该函数用于读取ecg信号，找到小波变换模极大序列(function to read the signals ecg find wavelet transform modulus maxima sequence)

经典子空间算法的完整实现，噪声消除效果比较好(an approach of speech enhancement algorithm)

stopsign detector train cascade on matlab

控制理论算法在采用状态反馈对目标进行控制时，往往忽略了时滞的存在。时滞往往存在于真实的系统中，而忽略时滞所设计的控制器在复杂的系统中可能会失效。本算法基于李雅普诺夫稳定性理论，以LMI的方式给出时滞系统的稳定性分析判据。(Time delay is widely existed in many engineering contrl systems whiile in many contrl theory and algothms time delay is ignored. This algorithm is given to analysis the stability of close- loop feedback time delay systems. And classical examples are given to demanstrate the effectiveness of this method.)

Viterbi algorythm implement for matlab simulink

numerical analysis of histogram

主要是采用贝叶斯分压缩感知算法，及相关的应用实例(BSC used in the compressed sensing)