MATLAB

A structure an motion toolkit in Matlab This document describes a set of Matlab functions for SAM (structure and motion recovery) its primary aim is to illustrate various methods developped over the past few years in this area

说明：  基于混沌序列和浮点小波变换的盲水印很好的研究生论文(Graduate thesis based on the blind watermarking good chaotic sequence and the floating-point wavelet transform)

Support for LG Electronics LGDT3304 and LGDT3305 - VSB QAM.

仿真FFT参数对采用FFT算法分析信号频谱的影响。产生频率分别为2Hz，2.05Hz的正弦波合成信号，采样频率＝10Hz。(Simulation of the influence of FFT parameters on the frequency spectrum of the signal using FFT algorithm analysis. The frequency of sine wave synthesis are respectively 2Hz, 2.05Hz signal, the sampling frequency is 10Hz.)

matlab高级讲义，其中包括各个实用例子的编程代码(matlab senior notes, including various practical examples of programming code)

模糊C均值聚类算法实现数据挖掘的matlab源代码(Fuzzy C-Means clustering algorithm for data mining matlab source code)

Vertical Channel Stabilization

基于MATLAB的夫琅禾费衍射演示。通过将衍射屏做成二值图并进行FFT变换得到衍射谱。(MATLAB-based Fraunhofer diffraction demonstration. Diffraction screen made by binary image and diffraction pattern for FFT transform. )

coler design segmentation The result of image segmentation is a set of segments that collectively cover the entire image, or a set of contours extracted the image (see edge detection). Each of the pixels in a region are similar with respect to some characteristic or computed property, such as color, intensity, or texture.

一种基于最小熵反褶积( ]8+83)3 6+D*(A4 Q20(+W(-)D8(+，]6Q) 的滚动轴承故障特征提取方法: 在利用 /X 模型去除齿轮啮合产生的确定性信号的基础上，对保留信号进行最小熵反褶积，增强冲击信号"该方法避免了传统轴承故障诊断方法中带通滤波器设计的难题，实车测试表明: 与共振解调技术相比，该方法提取的滚动轴承故障特征更加明显，更适合于工程应用"(Based on minimum entropy deconvolution (] 8+83) 3 6+D* (A4 Q20 (+W (-) D8 (+,] 6Q)' s fault feature extraction method: using/X model to remove the uncertainty generated signal gear on the basis of the retention signal minimum entropy deconvolution, and enhance the impact of signal " This method avoids the problems of traditional bearing fault diagnosis method of the bandpass filter design, real vehicle test showed that: compared with the resonance demodulation technology, which fault feature extraction method is more obvious, more suitable for engineering applications. " )