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ClassifierforIRISdata
用于对IRIS数据进行分类的各种分类器，用于对多维采样点进行无监督分类。可根据类别数修改分类器，模式识别作业的部分代码。(IRIS data for the various classification categories, for sampling points on the multi-dimensional non-supervised classification. Can be modified in accordance with several types of classifiers, pattern recognition part of the operating code.)
- 2009-07-08 17:37:42下载
- 积分：1
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ShowCorrespond
It can show the lines of corresponding points in two images for input points. If you have sift function, then you can utilize this function.
- 2011-06-01 14:34:25下载
- 积分：1
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train_RBF
在MATLAB平台上实现RBF神经网络训练，其中包含训练数据和测试数据(RBF neural network training to achieve the MATLAB platform, which includes training and testing data)
- 2015-04-12 16:52:57下载
- 积分：1
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MTLAB
讲解如何使用Matlab进行建模与仿真，并对仿真结果进行分析和可视化(Explain how to use Matlab for modeling and simulation, and simulation results for analysis and visualization)
- 2008-01-26 20:14:24下载
- 积分：1
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压缩感知matlab代码及说明 CS on SAR
压缩感知matlab代码及说明，适合初学者学习使用.关于SAR雷达，含7个代码(Compressed sensing matlab code and instructions for beginners to learn to use. Regarding SAR radar, with 7 code)
- 2021-03-27 19:09:12下载
- 积分：1
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SF_Spline
基于matlab的三次样条插值算法程序(Matlab based on the cubic spline interpolation algorithm procedure)
- 2007-12-05 18:21:48下载
- 积分：1
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artifact
Artifact removal of EEG signal EEG signal
- 2010-08-27 17:24:50下载
- 积分：1
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Chaboche-model-application
双线性随动 等向强化应变控制循环对称加载(Bilinear kinematic strain-controlled cyclic isotropic hardening symmetrical load)
- 2011-01-24 10:07:22下载
- 积分：1
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MATLABexcise
matlab 50道练习题，有助于新手快速提高编程和应用能力(matlab 50 道 exercises to help novice programming and ability to rapidly improve)
- 2011-05-11 22:42:48下载
- 积分：1
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聚类-k均值算法
说明： K-means算法是基于划分的思想，因此算法易于理解且实现方法简单易行，但需要人工选择初始的聚类数目即算法是带参数的。类的数目确定往往非常复杂和具有不确定性，因此需要专业的知识和行业经验才能较好的确定。而且因为初始聚类中心的选择是随机的，因此会造成部分初始聚类中心相似或者处于数据边缘，造成算法的迭代次数明显增加，甚至会因为个别数据而造成聚类失败的现象。(K-means algorithm is based on the idea of partitioning, so the algorithm is easy to understand and the implementation method is simple and feasible, but it requires manual selection of the initial number of clusters, that is, the algorithm is with parameters. The number of classes is often very complex and uncertain, so professional knowledge and industry experience are needed to better determine. Moreover, because the selection of initial clustering centers is random, some initial clustering centers will be similar or at the edge of data, resulting in a significant increase in the number of iterations of the algorithm, and even the phenomenon of clustering failure due to individual data.)
- 2020-06-21 17:40:01下载
- 积分：1
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