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image processing-histogram equalisation

gallstone segmentation and classification by kumares

说明：  用于检验两个时间序列是否具有格兰杰因果关系(Used to test whether two time series have Granger causality)

汉明码编码仿真程序，在Matlab环境下仿真，适用于初学者。(Hamming code encoding simulation program, in the Matlab simulation environment for beginners.)

压缩传感，压缩感知，压缩采样，稀疏表达，稀疏表示，的入门例子-compressive sensing compressed sensing(compressive sensing compressed sensing)

大规模MIMO中，有关于能效的相关文章 (MASSIVE mimo energy efficiency )

说明：  可以用于MATLAB基础学习以及基于MATLAB设计的其他软件的开发(MATLAB-based learning and can be used to design based on MATLAB and other software development)

利用matlab仿真金属圆柱体内电磁波分布，有助于掌握电磁波的传播情况。 把程序文档放入matlab的默认读取文档中，打开Cwave.m。Cwave.m是演示程序，由它调用其它函数。其中Z表示Kz*z，范围为0~2*pi。默认取2*pi为一个周期，num表示在一个周期内平均取多少个Kz*z值，默认为50(计算后每个值如Er都有五十幅图)。CWaveGuideCaculate函数用于计算Er,Efia,Hr,Hfia,Hz等值。CWaveGuideShow用于三维显示计算后得到的值，可以比较生动看到在一个周期内计算量的一连串的变换。(Matlab simulation using electromagnetic wave distribution inside the metal cylinder, is useful in the propagation of electromagnetic waves. To process the document read into matlab' s default document, open the Cwave.m. Cwave.m is the demonstration program, which will call other functions. Where Z said Kz* z, the range of 0 ~ 2* pi. The default access for a period of 2* pi, num, said the average take in a cycle number of Kz* z, default is 50 (calculated as per the value of Er has 50 chart). CWaveGuideCaculate function is used to calculate Er, Efia, Hr, Hfia, Hz equivalent. CWaveGuideShow been calculated for three-dimensional display of values, can be seen more vividly in a cycle of computation of a series of transformations.)

輸入點位於WGS84之大地經、緯度，可於命令窗顯示此點之卯酉圈曲率半徑N、子午圈曲率半徑M及平均曲率半徑R及此點之空間直角坐標X、Y及Z。(Input point is located in the WGS84 geodetic latitude and longitude can be displayed in the command window of the prime vertical radius of curvature point N, M meridian radius of curvature and the average radius of curvature R and the point of the space rectangular coordinates X, Y and Z.)

This file find the best coordination for a data set to reduce its dimension. Large data set,Dimension Reduction.