fiber_XPM

基于时空兴趣点的行为识别期刊论文。本为以时空特征点出发的三维兴趣点检测。(Based on time and space of interest points behavior identification journal articles.This is to start at space-time characteristics of three dimensional interest point detection.)

本程序按照胡广书《现代数字信号处理》书中的谱估计的内容仿真了各种经典谱估计方法以及现代谱估计方法（周期图法、BT法、welch法、自相关法、修正的协方差法、burg法），因为是课程作业，因此逻辑上写得十分简洁，适合初学者参考。(The program in accordance with the Hu-book of modern digital signal processing book spectral estimation simulation the various classical spectrum estimation methods, as well as the modern spectral estimation methods (periodogram, BT France, welch method, auto-correlation method, the modified covariance method , burg method), because the course work, so logically written very simple for beginners.)

遗传算法学习文档，是ppt课件资料，不错的课件！！(Study documents the genetic algorithm is ppt courseware information, good courseware! !)

基于matlab开发的通用有限元软件的源程序部分，最新版本(Matlab-based general-purpose finite element software development source part, the latest version)

wiggle plotting the segy format for seismic data set

说明：  Amplitude Moduladion code in matlab

mandelbrot 分型图的仿真与绘制。mandelbrot.m, mandelbrotdemo1.m, mandelbrotdemograph.fig(Mandelbrot type of simulation and rendering Fig. mandelbrot.m, mandelbrotdemo1.m, mandelbrotdemograph.fig)

说明：  经过我很长时间的努力，今天简单的实现正弦波仿真(make out sine wave)

经典的香农采样定理认为,为了不失真地恢复模拟信号,采样频率应该不小于奈奎斯特频率(即模拟信号 频谱中的最高频率)的两倍.但是其中除了利用到信号是有限带宽的假设外,没利用任何的其它先验信息.采集到 的数据存在很大程度的冗余.Donoho等人提出的压缩感知方法(Compressed Sensing或Compressive Sampling, CS)充分运用了大部分信号在预知的一组基上可以稀疏表示这一先验信息,利用随机投影实现了在远低于奈奎斯 特频率的采样频率下对压缩数据的直接采集.该方法不仅为降低采样频率提供了一种新思路,也为其它科学领域 的研究提供了新的契机.该文综述性地阐述了压缩感知方法的基本原理,给出了其中的一些约束问题和估计方法, 并介绍压缩感知理论的相关问题———矩阵填充,最后讨论了其未来可能的应用前景. (According to the conventional Shannon s sampling theorem,in order to represent the analog signal,the sampling rate should not be less than twice the Nyquist sampling rate.Howev- er,this theorem only makes use of the bandwidth information.As a result,the collected data contain many redundant information.The recently proposed sampling method,compressed sens- ing or compressive sampling(CS),can collect compressed data at the sampling rate much lower than that needed in Shannon s sampling theorem by exploring the compressibility of the signal. This paper presents a review on the basic theory of CS.Some of the restrictions and recovery methods in CS are also discussed.Finally,some potential applications based on CS are presented. )

matlab code for averaging data time series