eemd

设定循环检测次数，这里设为只循环一次 tip_l=1 设定hough变换的遍历步径 xl=30 ％设定线段起始点 xr=60 ％设定线段终止点(Set the number of cycle detection, here is set to cycle only once tip_l = 1 set hough transform Path traversal step xl = 30 set line segment starting point xr = 60 set line segment termination point)

GSCALE Scales the intensity of the input image. G = GSCALE(F, full8 ) scales the intensities of F to the full 8-bit intensity range [0, 255]. This is the default if there is only one input argument. G = GSCALE(F, full16 ) scales the intensities of F to the full 16-bit intensity range [0, 65535]. G = GSCALE(F, minmax , LOW, HIGH) scales the intensities of F to the range [LOW, HIGH]. These values must be provided, and they must be in the range [0, 1], independently of the class of the input. GSCALE performs any necessary scaling. If the input is of class double, and its values are not in the range [0, 1], then GSCALE scales it to this range before processing. The class of the output is the same as the class of the input. Copyright 2002-2004 R. C. Gonzalez, R. E. Woods, & S. L. Eddins Digital Image Processing Using MATLAB, Prentice-Hall, 2004 $Revision: 1.5 $ $Date: 2003/11/21 14:36:09 $

2dpca函数代码 通过调用运行 (2dpca function code by calling the run)

huffman compression using matlab

snake方法的主要局限性在于要求初始化要靠近期望的解和对边界的凹形部分的分割存在困难，GVF解决了这两个问题，并将其用于snake图像分割(The main limitation is the snake method requires initialization to be close to the desired solution and the boundary of the concave part of the division of the difficulty, GVF solve these two problems, and for the snake segmentation)

基于matlab语言的logistic回归分析程序 精确度(logistic regression analysis based on matlab language program accuracy)

数学建模中常用算法，应用十分广泛。此为此算法的Matlab程序，希望有用。(Commonly used mathematical modeling algorithm is widely used. The Matlab program for this algorithm, hope helpful.)

基于EMD和SVM的虹膜识别方法(医疗 图像匹配）(EMD and SVM based method for iris recognition (medical image matching))

说明：  用于合成孔径雷达成像的wk算法,成像质量要优于距离多普勒算法及线性调频变标算法。(wk algorithm of synthetic aperture radar imaging)

感知机学习的源代码，希望能对大家有学习上的帮助！(Perception of the source code of machine learning, we hope to help learning!)