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BP
说明: BP神经网络异或问题 使用说明:打开文件夹中的BP.m文件,在matlab中运行此m文件,即可在command window中得出结果。压缩包内附说明文件
(XOR problem of the BP neural network for use: Open the folder in BP.m file, run this m file in matlab to the outcome of the command window. Compression package containing the documentation)
- 2012-04-11 21:22:12下载
- 积分:1
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[Book]Robot-modeling-and-control
This book is concerned with fundamentals of robotics, including kinematics,
dynamics, motion planning, computer vision, and control.
- 2014-09-03 10:31:08下载
- 积分:1
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RBF.m
rbf RBF网络用于建模 ,过程很适合初学者懂的。很详细,很容易的!(RBF RBF network used for modeling, process is suitable for beginners understand. Very detailed, easy!
)
- 2011-11-13 18:24:28下载
- 积分:1
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VirtualTestTarget
Annotation for "virtual" implementation classes. These are classes that have the following attributes:.
- 2013-12-05 10:45:00下载
- 积分:1
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trust-region
信赖域法的MATLAB程序,包括2个子程序,性能超强!(the matlab program of Trust region, good!)
- 2020-06-30 09:40:02下载
- 积分:1
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DCT_DWT
利用离散余弦变换DCT和小波变换DWT实现对图片的变化域压缩并进行仿真以及性能分析(Using the discrete cosine transform DCT and wavelet transform DWT realization of the picture changes and simulated field compression and performance analysis)
- 2014-12-01 20:59:41下载
- 积分:1
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决策树分类实验(乳腺癌)
说明: 决策树分类程序,包含使用的数据集和运行结果(Decision tree classifier, including data sets used and running results)
- 2020-11-01 22:40:03下载
- 积分:1
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DSP_DTC
基于数字信号处理器(DSP)的异步电机直接转矩控制研究(DTC)
- 2010-07-11 14:14:44下载
- 积分:1
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PGM_Programming_Assignment_2
PGM-Programming_Assignment_2,概率图模型的网络公开课的第二次作业的代码matlab版本(Code matlab version PGM-Programming_Assignment_2, open class of probabilistic graphical network model' s second job)
- 2014-09-16 17:28:05下载
- 积分:1
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adaboost_version1e
这是一个经典的形变模型实施,在一个单一的文件用简单的可以理解的代码。
功能包括两部分一个简单的弱分类器和一个促进部分:
弱分类器试图找到最佳阈值的数据维数对数据进行分离成两个阶级1和1
要求的进一步提高分类器部分迭代,每一步是变化分类权重miss-classified例子。这造成了一连串的“弱分类器”,表现得像一个“强大分类器”
(This a classic AdaBoost implementation, in one single file with easy understandable code.
The function consist of two parts a simple weak classifier and a boosting part:
The weak classifier tries to find the best threshold in one of the data dimensions to separate the data into two classes-1 and 1
The boosting part calls the classifier iteratively, after every classification step it changes the weights of miss-classified examples. This creates a cascade of "weak classifiers" which behaves like a "strong classifier"
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- 2012-04-23 13:17:57下载
- 积分:1