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Numerical_recipes_pascal_code
说明: pascal programs for the book "numerical recipes in pascal".
- 2020-03-25 02:02:30下载
- 积分:1
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tsneMATLAB论文仿真代码
说明: 实现tSNE降维,已经封装完成,可以直接在matlab使用(Reducing dimension of tsne)
- 2019-12-19 20:48:09下载
- 积分:1
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灰色预测模型GM(1-N)
说明: 灰色预测模型GM(1,N),可以多因素分析,可对未来数据进行预测。
程序可直接运行,可以更换数据。
预测未来数据时,只需修改T值,以及因变量数据;否则T=0即可。
例如,预测未来2个数据,T=2.
输入数据:因变量x1为400.因变量x2为50;因变量x1为450.因变量x2为90。(The grey prediction model GM (1, n) can analyze many factors and predict the future data.
The program can run directly and change data.
When predicting future data, only the T value and dependent variable data need to be modified; otherwise, t = 0.
For example, predict 2 data in the future, t = 2
Input data: the dependent variable X1 is 400, the dependent variable X2 is 50, the dependent variable X1 is 450, and the dependent variable X2 is 90.)
- 2020-01-04 21:01:43下载
- 积分:1
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ChinaMeteorologicalDataHandler
说明: 对中国气象网的气象地面日值数据进行合并标准化处理,可以提取指定站点的气象信息,实测好用(By combining and standardizing the meteorological daily data of China Meteorological Network, the meteorological information of designated stations can be extracted, which is easy to use)
- 2020-03-10 14:02:06下载
- 积分:1
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相关系数计算
说明: python程序计算皮尔逊相关系数、最大信息系数以及灰色关联度(Pearson correlation coefficient, maximum information coefficient and grey correlation degree were calculated by Python program)
- 2020-09-19 12:57:57下载
- 积分:1
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小波神经网络
说明: 一些基础的小波神经网络用于基础的分类代码,不是很复杂(Some basic wavelet neural networks are used for basic classification codes, which are not very complicated)
- 2020-08-13 14:28:11下载
- 积分:1
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POWELL
说明: powell线性搜索法,求解极小化问题。内含说明文档,源数据(Powell linear search method is used to solve the minimization problem. Include description document, source data)
- 2020-02-26 20:16:17下载
- 积分:1
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构造均匀设计方法
说明: method1_glp.m是好格子点法构造均匀设计,method2_pglp.m是方幂好格子点法构造均匀设计,适用于试验点较多的情况(good lattice points method to construct uniform design)
- 2020-02-23 12:04:03下载
- 积分:1
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光电编码器
该程序完成了光电编码器的功能,有波形设计,四细分,正传加一,反转减一,有输入输出波形
- 2022-03-20 13:54:06下载
- 积分:1
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MixedVineToolbox-master
说明: 混合藤Copula工具箱
A. Onken and S. Panzeri (2016). Mixed vine copulas as joint models of
spike counts and local field potentials. In D. D. Lee, M. Sugiyama,
U. V. Luxburg, I. Guyon and R. Garnett, editors, Advances in Neural
Information Processing Systems 29 (NIPS 2016), pages 1325-333.(Mixed-Vine Copula Toolbox
A. Onken and S. Panzeri (2016). Mixed vine copulas as joint models of
spike counts and local field potentials. In D. D. Lee, M. Sugiyama,
U. V. Luxburg, I. Guyon and R. Garnett, editors, Advances in Neural
Information Processing Systems 29 (NIPS 2016), pages 1325-333.)
- 2020-10-03 11:03:13下载
- 积分:1