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MIT_matlab
一份麻省理工大学1999年的信号与系统的matlab教程简介,希望对刚学习matlab的朋友管用(A Massachusetts Institute of Technology in 1999 signals and systems matlab tutorial introduction to just want to learn useful matlab friend)
- 2010-07-19 00:13:29下载
- 积分：1
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Kmeans
Kmeans algorithm is the most popular algorithm for clustering
- 2011-02-14 16:53:06下载
- 积分：1
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zhuomian
这是关于正交解调与正交调制的一些matlab源代码 呵呵(This is about orthogonal demodulation and orthogonal modulation of some of the matlab source code ha ha
)
- 2013-01-07 15:11:54下载
- 积分：1
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SVM
In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that assigns new examples into one category or the other, making it a non-probabilistic binary linear classifier. An SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on which side of the gap they fall on.
- 2014-12-14 21:33:26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
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Brain-Tumour
This is a matlab project in which application detect the brain tumour.
- 2014-11-11 14:32:27下载
- 积分：1
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topnology
MATLAB做网络优化，先生成一个随机的邻接矩阵，然后画出改图。(MATLAB to do network optimization, sir into a random adjacency matrix, and then draw the reform plan.)
- 2010-09-03 23:43:12下载
- 积分：1
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task-parameterized-GMM-v1.0
GMM program that will help to implement the concept of gaussian mixture model
- 2013-02-12 17:39:57下载
- 积分：1
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wind_100_parell
6台100kw风力机组并网运行MATLAB模型，可移植性强，适用于我国微网系统模型研究。(6 sets of 100kW wind power generator MATLAB model, strong portability, is suitable for our country on micro network system model.)
- 2021-02-26 10:49:37下载
- 积分：1
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L_D_sim
功能描述：测试Levinson-Durbin算法
文件名：L_D_sim.m
测试用例：
(1)x(n)+0.81*x(n-2)=u(n)，u(n)为高斯白噪声
(2)x(n)=u(n)+u(n-1)+u(n-2),u(n)为高斯白噪声
文件输出：两种测试用例情况下的功率谱
调用函数：function [A,E] = Levinson_Durbin_Algo(R,P)
被调用：无
作者：mingcheng
编写时间：2009-11-13
修改时间：2009-11-13
版本：V1.0 ( Function Description: Test Levinson-Durbin algorithm file name: L_D_sim.m test case: (1) x (n)+0.81* x (n-2) = u (n), u (n) is Gaussian white noise (2) x (n) = u (n)+ u (n-1)+ u (n-2), u (n) is Gaussian white noise file output: two tests use case in case of power spectrum call the function: function [A, E] = Levinson_Durbin_Algo (R, P) is called: No of: mingcheng write time :2009-11-13 modified :2009-11-13 version: V1.0 )
- 2010-07-11 12:19:03下载
- 积分：1
