LMS2dim2u

我自己写的小波神经网络的Matlab程序，包含了单维的高维的两种网络模型，比较全面，而且代码中加入开发的初始化算法，使用时只需要更换训练样本就可以了。希望对论文写作有所帮助(I wrote it myself WNN Matlab procedures, includes a one-dimensional two high-dimensional network model, a more comprehensive, but also to add code to initialize the development of algorithms, using only training samples need to replace it. Writing wish to be helpful)

Used to select common points on two images for morphing. Data saved as a *.mat file afterwards.(Used to select common points on two images for morphing. Data saved as a *.mat file afterwards.)

normalizing the sign in matlab

Matlab mallat分解重构 小波谱分析mallat算法经典程序(Algorithm for spectral analysis mallat small classic program)

二次规划程序(Quadratic programming)在matlab的源代码(Quadratic programming codes in matlab)

Relief算法中特征和类别的相关性是基于特征对近距离样本的区分能力。算法从训练集D中选择一个样本R，然后从和R同类的样本中寻找最近邻样本H，称为Near Hit，从和R不同类的样本中寻找最近样本M，称为Near Miss，根据以下规则更新每个特征的权重： 如果R和Near Hit在某个特征上的距离小于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻是有益的，则增加该特征的权重；反之，如果R和Near Hit在某个特征上的距离大于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻起负面作用，则降低该特征的权重。(The correlation between feature and category in Relief algorithm is based on distinguishing ability of feature to close sample. The algorithm selects a sample R from the training set D, and then searches for the nearest neighbor sample H from the samples of the same R, called Near Hit, and searches for the nearest sample M from the sample of the R dissimilar, called the Near Miss, and updates the weight of each feature according to the following rules: If the distance between R and Near Hit on a certain feature is less than the distance between R and Near Miss, it shows that the feature is beneficial to the nearest neighbor of the same kind and dissimilar, and increases the weight of the feature; conversely, if the distance between R and Near Hit is greater than the distance on R and Near Miss, the feature is the same. The negative effect of nearest neighbor between class and different kind reduces the weight of the feature.)

3D shape reconstruction matlab code. It used shape from defocus technique with least squares. You can reconstruct 3D shape with only two different depth images.

This function transforms a three-phase unbalanced phasor into its

target tracking codes

Servo motors and industrial