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The_Steep_Descent_Method
The Steep Descent Method
- 2009-11-30 22:14:16下载
- 积分:1
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Support-Vector-Machine
非线性回归用支持向量机通用MATLAB源码(Support Vector Machine for Nonlinear Regression)
- 2015-02-25 19:37:52下载
- 积分:1
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chap4
雷达模糊函数 等高图,gui界面,函数,MATLAB 仿真(Radar fuzzy function contour map, GUI interface, function)
- 2020-06-21 09:00:01下载
- 积分:1
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mat2
这是MATLAB的一维插值的应用,数模培训的必要内容(This is the MATLAB interpolation of one-dimensional applications, a number of essential elements in training mode)
- 2007-12-10 15:04:03下载
- 积分:1
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createButtonLabel
buttonIcon = createButtonLabel(string,PVs,figOpt)
Have you ever been frustrated by an inability to label a vertically oriented pushbutton or uicontrol with a string? This function is for you!
All valid Parameter-Value pairs, INCLUDING TEXT ROTATION, are supported. Note that this function requires the Image Processing Toolbox, and that it triggers the creation of a temporary figure, which will be momentarily visible during button-label creation.
- 2009-10-21 15:19:29下载
- 积分:1
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Multipath-Impulse-Response
提出了一种递归方法,用来计算当室内反射光源视为Lambertian光源时,室内自由空间信道的冲击响应。(A recursive method for evaluating the
impulse response of an indoor free-space optical channel with
Lambertian reflectors.)
- 2011-04-28 12:03:36下载
- 积分:1
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PMSM-good
各种可直接运行的matlab simulink的电机模型(Variety can be directly run matlab simulink motor model)
- 2013-11-21 10:11:40下载
- 积分:1
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Practice2
根据学生两次考试成绩的数据来预测学生是否能被大学录取,用逻辑斯蒂回归算法实现,分别执行梯度下降算法、随机梯度下降算法、牛顿法(According student test scores twice to predict whether the student can be admitted to universities, implemented in logistic regression algorithm.)
- 2020-12-17 20:39:11下载
- 积分:1
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gansao
小波包分析提取振动信号中的特征频率,含噪脉冲信号进行相关检测,二维声子晶体FDTD方法计算禁带宽度的例子。( Wavelet packet analysis to extract vibration signal characteristic frequency, Noisy pulse correlation detection signal, Dimensional phononic crystals FDTD method calculation examples band gap.)
- 2016-05-29 16:46:26下载
- 积分:1
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svm2
说明: 支持向量机最初用来解决模式识别问题,目的是发现泛化性能好的决策规则。然而,随着Vapnik的 不敏感损失函数的引入,支持向量机已经扩展为解决非线性回归估计问题,而且与神经网络方法相比,有着显著的优越性,被认为是人工神经网络方法的替代方法,已经成为目前机器学习领域的研究热点和焦点。(Support vector machine (SVM) was originally used to solve the problem of pattern recognition. However, with the introduction of Vapnik's insensitive loss function, support vector machine (SVM) has been extended to solve the problem of nonlinear regression estimation. Compared with neural network method, support vector machine (SVM) has obvious advantages. It is considered as an alternative method of artificial neural network method, and has become the research hotspot and focus in the field of machine learning.)
- 2020-07-01 14:07:02下载
- 积分:1