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Staticvarcompensator
Static var compensator model matlab simulink model
- 2010-05-12 21:54:15下载
- 积分：1
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chap2
滑模变结构控制的基础理论，很适合初学者使用和学习(The sliding mode variable structure control of the basic theory, it is suitable for beginners to use and learn)
- 2012-05-30 10:14:56下载
- 积分：1
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regiongrowing
Region Growing algorithm
- 2012-07-23 18:59:10下载
- 积分：1
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10012317071b3663dc976f6dc6
matlab做时间序列分析的一本非常好的参考书。matlab在时间序列分析中的应用。(Time series analysis matlab to do a very good reference book. matlab in time series analysis application.)
- 2013-11-17 22:46:59下载
- 积分：1
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erwei
彩色图像变成灰色图像，并对其进行直方图分析，二维直方图分析以及二维直方图的OTSU处理(Color images into gray image and its histogram analysis, OTSU processing of two-dimensional and two-dimensional histogram histogram analysis)
- 2013-12-19 13:56:24下载
- 积分：1
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用于计算地震作用下单自由度结构的响应和响应
说明： 用于计算地震作用下单自由度结构的响应和响应谱(Used to calculate the response and response spectrum of a single degree of freedom structure under earthquake action)
- 2020-06-23 03:00:02下载
- 积分：1
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shiermaibo2
基于matlab的十二脉波整流电路的仿真(Twelve pulse rectifier circuit )
- 2021-01-17 14:08:50下载
- 积分：1
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fuzzy
模糊控制得matlab仿真程序，主要做模糊控制仿真学习使用简单易懂。(Fuzzy control with matlab simulation program, the main job of fuzzy control simulation study using simple to understand.)
- 2009-10-12 21:31:26下载
- 积分：1
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test
GMM的matalab实现，通过对多个语种进行训练，然后得出每个语种的GMM模型，最终用于语种识别(GMM' s matalab achieved through training of more than one language, then come to the GMM model for each language, and ultimately for identifying languages)
- 2011-08-04 20:55:38下载
- 积分：1
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dace_kriging
说明： 克里格法（Kriging，KRG）是由法国统计学家 Matheron 于 1963 年提出的，为纪念南非金矿工程师 Krige（Krige, 1951）曾于 1951 年使用回归方法对空间场进行预测的开创性研究，Matheron 将该方法命名为 Kriging，最开始该方法常被用于对矿产储量分布情况进行预（Matheron, 1963）。目前该方法作为最常用的空间插值算法，被广泛应用于地理科学、环境科学、大气科学等研究中。(Kriging (KRG) method was proposed by Matheron, a French statistician, in 1963. In order to commemorate the pioneering research of Krige (1951), a gold mine Engineer in South Africa, who used regression method to predict the spatial field in 1951, Matheron named this method Kriging. At first, this method was often used to predict the distribution of mineral reserves (Matheron, 1963) . At present, as the most commonly used spatial interpolation algorithm, this method is widely used in geographical science, environmental science, atmospheric science and other research.)
- 2020-02-10 17:27:01下载
- 积分：1
