matlabProgramming-Fundamentals

本文为介绍matlab图像处理方面的电子书(In this paper, for the introduction matlab image processing aspects of e-books)

压缩包里有OFDM信号的分析，频谱，星座图，加窗(Compression bag with OFDM signal analysis, spectrum, constellation, plus window)

用凯瑟窗设计一个数字带通滤波器，设计指标为 低阻带：ws1=0.2pi,as=70dB, 低通带：wp1=0.35pi,ap=1dB, 高通带：wp2=0.65pi,ap=1dB, 高阻带：ws2=0.8pi,as=60dB(Kaiser window design with a digital band-pass filter design specifications for the Low resistivity zone: ws1 = 0.2pi, as = 70dB, Low-pass band: wp1 = 0.35pi, ap = 1dB, High-pass band: wp2 = 0.65pi, ap = 1dB, Impedance with: ws2 = 0.8pi, as = 60dB )

小船过河模型，在船速与水速已知情况下，作出小船航行轨迹(Boat to cross the river model, speed and water speed in the circumstances known to make the boat sail track)

说明：  用的逐步定线方法，在解决这个问题中并不是一个很有效的方法，我想最好的方法为Dijkstra，但Dijkstra编起来比较简单（已有源程序，只须改变权矩阵），没有再进行练习。 程序编制的比一些比赛论文中的要精细一些，但结果不是很好。(The progressive alignment method used in solving this problem is not a very effective way, I think the best way to Dijkstra, but it is relatively simple Dijkstra Code (has source code, just change the weight matrix), no further to practice. Programming than some games should be fine in a number of papers, but the results are not very good.)

rgb2lab：rgb颜色空间向lab颜色空间转换的matlab代码，对此变换要使用不求甚解的童鞋们可以直接调用~(rgb2lab：colorspace of rgb translate to colorspace of lab。Just for the beginner~)

说明：  基于matlab小波变换分解信号并重构算法过程分析及代码(Signal based on wavelet transform decomposition and reconstruction algorithm matlab process analysis and code)

Spectral Subtraction Noise reduction algorithm

结合DOA估计中最常用的两个算法MUSIC和ESPRIT的优点，富有MATLAB如按程序(Combined with the most common advantages of the two algorithms MUSIC and ESPRIT DOA Estimation)

说明：  它主要研究的是多因变量对多自变量的回归建模，特别当各变量内部高度线性相关时，用偏最小二乘回归法更有效。另外，偏最小二乘回归较好地解决了样本个数少于变量个数等问题。 偏最小二乘法是集主成分分析、典型相关分析和多元线性回归分析3种分析方法的优点于一身。它与主成分分析法都试图提取出反映数据变异的最大信息，但主成分分析法只考虑一个自变量矩阵，而偏最小二乘法还有一个“响应”矩阵，因此具有预测功能。(It is mainly a result of the study is a multi-variable regression modeling and more independent variables, especially when the internal height of each variable linear correlation, partial least squares regression method is more effective. In addition, partial least squares regression solves the number of samples is less than the number of variables and other issues. Partial least squares method is a set of principal component analysis, canonical correlation analysis and multiple linear regression analysis of the advantages of the three methods in one. It is the principal component analysis are trying to extract the maximum information reflects data variability, but the principal component analysis considers only one independent variable matrix, and partial least squares and a &quot response&quot matrix, predictive capabilities.)