VLsift

说明：  Parzen窗法，由样本求概密估计，例为一维正态分布和双峰均匀分布，内附随机数生成的原理说明。( window method, by the sample density estimate for estimated Example for one-dimensional normal distribution and bimodal uniform distribution, random number generator containing a description of the principle.)

高斯法求解方程，在matlab中建立，求解方程并显示运算时间结果，用于对高斯法有一个更直观的认识。(Gauss method for solving equations, established in matlab, solving equations and displays the computation time results for the Gaussian method has a more intuitive understanding.)

基于BOOST斩波电路的MTALAB仿真，仿真结果正确，开关电源设计必备仿真(BOOST chopper MTALAB based simulation, simulation results are correct, switching power supply design must Simulation)

matlab版本的数字信号处理，适合初学的人。(matlab version of the digital signal processing, suitable for beginners person.)

image sharpening using matlab

一次matlab课程作业,使用了GUI程序，非常基础，适合初学者，不错的启蒙程序。(A matlab course work, the use of a GUI program, very basic, suitable for beginners, a good program of enlightenment.)

EM算法在概率图中的应用，在计算机视觉中也用用到！(EM algorithm in the application of probability map, is also used in computer vision is used!)

小波融合程序，MATLAB下拥有较好的融合效果！(Wavelet fusion procedures, MATLAB has a better integration of results!)

这是一篇SCI文章《改善字典学习：多字典更新和系数重用》里的Matlab代码，包含了OMP、Batch-OMP、CoROMP等匹配跟踪算法代码以及改进的K-SVD字典学习算法代码，是图像稀疏表示研究方向重要的源代码，有助于大家学习和改进。(This file folder reproduces the Figures for paper:"Improving Dictionary Learning: Multiple Dictionary Updates and Coefficient Reuse".It contains codes of the OMP, Batch code- OMP, CoROMP matching pursuit algorithm and improved K- SVD dictionary learning algorithm ,This is the important source code of image sparse representation ,which can help you learn and improve. )

关于柴油机与液力变矩器匹配的一些论文，很好的知识(Many designs of rotary engine were proposed in the past 100 years, including the recent rotary vane concept 10 , but only the gasoline Wankel engine has become a production success. This has good power-weight ratio, inherent balance, and smoothness, but suffers from reduced effi ciency, sealing, and emissions prob-lems, particularly of unburned hydrocarbons 1)