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mean.shift.matlab
说明: 利用mean shift实现图像分割和平滑(utilize the mean shift method to achieve image segementation and flatness.)
- 2010-04-11 12:58:37下载
- 积分:1
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Em
说明: 根据有限混合模型的数据分类的程序,同时附实验报告(Hybrid model based on limited data classification procedures, test reports with)
- 2011-09-22 09:07:14下载
- 积分:1
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Chapter-12-Factor-Analysis
因子分析,有实例,推荐测试,下载。科学输出处理必备!(Factor analysis, there are examples of recommended tests, download. Scientific output processing necessary!)
- 2013-10-05 09:50:12下载
- 积分:1
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ANTE
蚁群算法 无批次 生产流程问题(Ant Algorithm No
batch production process)
- 2013-04-06 14:22:54下载
- 积分:1
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XBee-Quick-Reference-Guide
X-bee reference guide. to interface with other modules in PDF formate..
- 2015-02-21 13:05:11下载
- 积分:1
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bldcm
无刷永磁直流电动机模型,可用于飞轮储能。基于matlab的simulink建立。(Brushless permanent magnet DC motor model can be used for flywheel energy storage. Established based on the matlab simulink.)
- 2011-08-28 08:21:28下载
- 积分:1
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LADRC
线性自抗扰算法样例;采用matlab脚本文件实现(Examples of linear ADRC algorithm)
- 2021-01-22 11:28:46下载
- 积分:1
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Medoidshift
中心点漂移是一种非监督聚类算法(与k-means算法相似,但应用范围更广些),可用于图像分割,基于Matlab实现的源码。
MedoidShift is a unsupervised clustering algorithm(similar to k-means algorithm, but can be used in border application fields), can be used for image segmentation. Included is the Matlab implementation source code.(Center drift is a non-supervised clustering algorithm (k-means algorithm with the similar, but more a wider range of applications), can be used for image segmentation, based on the realization of the source Matlab. MedoidShift is a unsupervised clustering algorithm (similar to k-means algorithm, but can be used in border application fields), can be used for image segmentation. Included is the Matlab implementation source code.)
- 2008-01-21 15:09:00下载
- 积分:1
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ann-bp
说明: 人工神经网络MATLAB源程序:此MATLAB程序用于人工神经网络(ANN MATLAB source : This MATLAB procedures for artificial neural network)
- 2006-03-25 08:46:48下载
- 积分:1
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matlab(bp)
matlab神经网络应用设计,里面随有详细代码(Matlab neural network application design, which with a detailed code)
- 2006-11-10 02:09:00下载
- 积分:1