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sanchongDC
三重化双向buck—boost电路 实现三重化dc dc双向buck—boost电路的功能(Triple bi-directional buck-boost circuit)
- 2020-10-16 21:47:28下载
- 积分:1
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0.2-alpha
documentclass{beamer}
usepackage[frenchb]{babel}
usepackage[T1]{fontenc}
usepackage[latin1]{inputenc}
usetheme{Warsaw}
egin{document}
egin{frame}
Voici votre première page de présentation en LaTeX !
end{frame}
end{document}
- 2012-09-16 20:26:51下载
- 积分:1
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dianlixitong
这是电力系统相关的一个课程设计,运用的编程语句相对比较简单、易懂。适合对Matlab不是很熟练的学子(This is a curriculum-related power system design, the use of programming statements is relatively simple, understandable. Suitable for Matlab is not very skilled students)
- 2013-11-28 09:55:46下载
- 积分:1
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Gestion
Ce programme a pour rô le la gestion d une scolarité, il a plusieurs fonctionnalités : ajout/suppression d un enseignant, ajout/suppression d un étudiant, ajout/suppression d un module, ajout/suppression d une filière.
- 2015-04-16 07:07:04下载
- 积分:1
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Gabor-Filter
This code is used for extracting texture features in an image
- 2014-01-24 18:20:08下载
- 积分:1
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AD835
说明: AD835的仿真模型,用matlab的工具箱,simulink搭建的(AD835 simulation model, using matlab toolbox, simulink built)
- 2008-09-24 17:30:28下载
- 积分:1
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parameter-estimation
说明: 时间序列分析中参数估计方面的实现,在matlab环境下实现的代码(parameter estimation)
- 2011-03-10 19:39:49下载
- 积分:1
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zhuangjiaPID
专家PID程序主要是针对受控对象和各种规律已知情况的一种智能程序(Expert PID program is mainly directed against the known laws of the controlled object and a variety of circumstances an intelligent process)
- 2011-04-20 08:47:22下载
- 积分:1
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qlearning
q-learning的相关例程,可供大家学习了解使用(about q-learning)
- 2014-11-04 10:23:37下载
- 积分:1
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半监督分类算法
半监督学习(Semi-Supervised Learning,SSL)是模式识别和机器学习领域研究的重点问题,是监督学习与无监督学习相结合的一种学习方法。半监督学习使用大量的未标记数据,以及同时使用标记数据,来进行模式识别工作。当使用半监督学习时,将会要求尽量少的人员来从事工作,同时,又能够带来比较高的准确性,因此,半监督学习目前正越来越受到人们的重视。(Semi-Supervised Learning (SSL) is a key issue in the field of pattern recognition and machine learning. It is a learning method combining supervised learning with unsupervised learning. Semi-supervised learning uses a large number of unlabeled data, as well as labeled data, for pattern recognition. When using semi-supervised learning, it will require as few people as possible to work, and at the same time, it can bring relatively high accuracy. Therefore, semi-supervised learning is receiving more and more attention.)
- 2021-04-12 11:28:57下载
- 积分:1