Henderson_mixed

LTE的入门资料，介绍整个LTE系统的组成和工作原理，经典书籍，值得一读(LTE introductory information on the composition of the LTE system and working principle of the classic books worth reading)

这是一篇关于用MATLAB实现动态规划顺序算法的一个论文性质的文章(This is an article on using MATLAB in order to achieve dynamic programming algorithm is the nature of a paper article)

matlab codes for adaptive filter FIR

simulates the behavior of an asset value over time

说明：  一个用matlab编写的构建合成地震记录和剖面的工具箱集合，也包括多个小波函数和互动的小波编辑器(Written by matlab build a synthetic seismogram and profile collection kit, including a number of wavelet functions and wavelet interactive editor)

KNN k s nearest neighbor algorithm(KNN k' s nearest neighbor algorithm)

说明：  matlab语言的人工蜂群算法，包括最初版本和改进版两版(Matlab language artificial bee colony algorithm, including the initial version and the improved version)

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.

关于滑动平均主成分分析（MA-PCA）的MATLAB代码。(Principal component analysis on the moving average (MA-PCA) MATLAB code.)

About the h.264 matlab code in video compression