multipath_test

matlab的 视觉 程序 可以带有一个高斯滤波(Matlab visual procedures with a Gaussian filter)

说明：  Dsp中的Matlab ， AFD_BUTT.M AFD_CHB1.M AFD_CHB2.M(Dsp of Matlab, AFD_BUTT.M AFD_CHB1.M AFD_CHB2.M)

说明：  Matlab精彩编程一百例，图形图像处理，函数处理(Exciting one hundred cases of Matlab programming, graphics, image processing, function handle)

this file is an ac to ac controller. you can control the output by adjusting the firing angle of the SCR.

插值计算 底质遥感反射率 水面之下遥感反射率(interp1 bottom reflectance underwater irradaince reflectance)

信道估计算法及实现,matlab编写(Channel estimation algorithm and realize, matlab prepared)

matlab的卡尔曼滤波预测算法例子，希望对大家有帮助(matlab prediction algorithm of the Kalman filter example, we would like to help)

matlab 多维小波工具箱 有线性卷积 三维的小波变换，逆变换等等 (matlab multi-dimensional wavelet toolbox has three-dimensional linear convolution of wavelet transform, inverse transform and so on)

伪wigner分布，强大好用。修改输入和输出就能很快地使用。(Pseudo wigner distribution, a powerful easy to use. Modify the input and output can be quickly used.)

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.)