Multi-target

利用Matlab提取图片中的数据 从事科研或者工程的人员在文档撰写过程中，常需要将文献中的曲线与自己的结果对比，为获取原始数据，一种常用的办法是手动描点，即将原始曲线放大然后打印出来，选取一定数量的点，读出其横纵坐标，然后重绘。对于较为平坦的曲线，这种方法当然可行，但当曲线数量增加，曲线变化复杂，这种方法工作量可想而知。前段时间由于原始数据丢失，仅剩几十幅图片，本人尝试过手动描点，经历几个小时奋战，实在无法继续，索性转向matlab，借助其强大的数据处理能力，编写了两个GUI的小软件image2data、data_poly提取数据，如今大功告成，遂于大家分享。(Using Matlab to extract picture data in scientific research or engineering personnel in the process of writing documentation, often need to curve in the literature comparing the results to obtain the original data, a common approach is described in the manual, is about the original amplification curve and then print it out, select a certain number of points, read out its horizontal and vertical coordinates, and then redraw. For a flatter curve, this approach is of course possible, but when the increase in the number of curves, the complexity of the curve, this method can imagine the workload. Some time ago due to the loss of original data, except for the dozens of pictures, I tried manually tracing point, after several hours of fighting, I can not continue to simply turn to Matlab, with its powerful data processing capabilities, the preparation of two GUI software image2data, data_poly extract data, and now you' re done, then share with you.)

图像去雾算法Matlab代码，可以实现图像去雾处理(Haze remove code)

该程序能够实现信号的离散傅里叶变换，且算法简单，容易实现。(The program enables the signal discrete Fourier transform, and the algorithm is simple and easy to implement.)

这篇文章是盲信号处理，因为是英文文章，所以大家看内容就好了。(Principal component analysis (PCA) is a mainstay of modern data analysis- a black box that is widely used but poorly understood. The goal of this paper is to dispel the magic behind this black box. This tutorial focuses on building a solid intuition for how and why principal component analysis works furthermore, it crystallizes this knowledge by deriving from simple intuitions, the mathematics behind PCA . This tutorial does not shy away from explaining the ideas informally, nor does it shy away from the mathematics. The hope is that by addressing both aspects, readers of all levels will be able to gain a better understanding of PCA as well as the when, the how and the why of applying this technique.)

simulink files for fsk modulation and demodulation

四旋翼飞行器入门材料，由浅入深，适合初学者(Four-rotor entry materials, Deep, suitable for beginners)

一个完整的OFDM系统的MATLAB仿真，有注解(simulation of OFDM system using MATLAB)

A sample code on fractional order derivatives

建立了铰接车六自由度线性模型，用于分析半挂汽车等铰接列车的动力学分析(Six degrees of freedom to establish a linear model articulated truck, trailer and automobile for the analysis of the dynamics of articulated trains)

说明：  这是一个拉格朗日的插值算法的matlab的实现(This is a Lagrange interpolation algorithm to achieve the matlab)