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MATlab_diff_int
用MATLAB实现动态系统的求导与积分函数(MATLAB diff and int)
- 2010-08-25 14:52:20下载
- 积分：1
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matlable
MATLAB 语言入门资料，高校老师编写(MATLAB language introductory information on the preparation of college teachers)
- 2009-05-15 23:22:17下载
- 积分：1
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FOUR_ICA
利用四阶统计量求三个信号混合后的独立成分，包括超高斯、高斯和亚高斯信号(Demand the use of three fourth-order statistics of independent mixed signal components, including the super-Gaussian, Gaussian and sub-Gaussian signal)
- 2010-12-28 16:02:24下载
- 积分：1
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color-cluster_5.m
clustering with matlab
- 2013-02-12 14:30:08下载
- 积分：1
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Polynomial-non-polynomial
多项式和非多项式曲线拟合，MATLAB的经典案例 (Polynomial and non polynomial curve fitting)
- 2013-11-30 21:30:23下载
- 积分：1
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DA_SYSTEM
Google KML Contour Plot / Wind Arrows Plot
- 2014-01-02 11:15:28下载
- 积分：1
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S-Isomap
非线性降维, 使用者必须自己准备数据，可以对立面的参数进行修改(nonlinear dimesion reduction,This package is free for academic usage. You can run it at your own risk.)
- 2021-04-11 16:48:58下载
- 积分：1
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Multi-Sensor-Data-Fusion-with-MATLAB
多传感器数据融合的国外经典教材，结合matlab软件，讲解的十分具体(A book of Multi-Sensor Data Fusion with MATLAB)
- 2012-01-29 20:06:31下载
- 积分：1
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AdaboostROC
对于分类对象 （汽车、 行人...） 我们需要相关的分类器。Adaboost 是残败的分类器可以得到高的相关分类
- 2023-02-28 00:05:04下载
- 积分：1
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fs_sup_relieff
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.)
- 2018-04-17 14:41:55下载
- 积分：1
