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Description: 通过在MATLAB平台上比较BP神经网络的三种训练方法－trainbr traingdm trainlm.并且网络中加入噪音！-through MATLAB platform comparison BP neural network training method for the three-trainbr traingdm trainlm. Network and add noise!
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Size: 1179 |
Author: 江宏伟 |
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Description: L-M优化算法（trainlm）和贝叶斯正则化算法（trainbr）
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Size: 1071 |
Author: ouyinghua |
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Description: 通过在MATLAB平台上比较BP神经网络的三种训练方法－trainbr traingdm trainlm.并且网络中加入噪音！-through MATLAB platform comparison BP neural network training method for the three-trainbr traingdm trainlm. Network and add noise!
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Size: 1024 |
Author: 江宏伟 |
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Description: L-M优化算法（trainlm）和贝叶斯正则化算法（trainbr）-LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr)
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Size: 1024 |
Author: ouyinghua |
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Description: 采用动量梯度下降算法训练BP网络，采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络-Gradient descent algorithm using momentum BP network training, using two training methods, namely, LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr), to facilitate the training of BP network
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Size: 3072 |
Author: 闫薇 |
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Description: 采用贝叶斯正则化算法提高BP网络的推广能力。在本例中，将采用两种训练方法，即L-M优化算法（trainlm)和贝叶斯正则化算法（trainbr),用以训练BP网络，使其能够拟合某一附加有白噪声的正弦样本数据。-The use of Bayesian regularization algorithm for BP network to improve generalization ability. In this case, two types of training methods will be used, that is, LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr), to facilitate the training of BP network to enable it to fit attached to a white noise of the sinusoidal sample data.
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Size: 1024 |
Author: qiulan |
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Description: 采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr）-Using two training methods, namely, LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr)
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Size: 3072 |
Author: chen |
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Description: 采用贝叶斯正则化算法（抑制过拟合）提高 BP 网络的推广能力，采用两种训练方法，
即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络；-Bayesian regularization algorithm (inhibition of over-fitting) to improve the generalization ability of BP network, using two training methods, that LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr), to train BP network
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Size: 1024 |
Author: liuwei |
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Description: 采用贝叶斯正则化算法提高 BP 网络的推广能力。在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正
则化算法（trainbr），用以训练 BP 网络，使其能够拟合某一附加有白噪声的正弦样本数据。-Use Bayes to train BP network
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Size: 1024 |
Author: 肖木 |
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Description: 贝叶斯正则化算法提高 BP 网络，L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络-Bayesian regularization algorithm to improve BP network
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Size: 1024 |
Author: 陶西柱 |
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Description: 采用贝叶斯正则化算法提高 BP 网络的推广能力。 在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络，使其能够拟合某一附加有白噪声的正弦样本数据。-Bayesian regularization algorithm to improve the generalization ability of BP network. In this example, we use two training methods, namely LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr), to train BP network so that it can fit a sine additional white noise sample data.
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Size: 1024 |
Author: 张 |
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Description: 例1 采用动量梯度下降算法训练 BP 网络。
例2 采用贝叶斯正则化算法提高 BP 网络的推广能力。在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络，使其能够拟合某一附加有白噪声的正弦样本数据。-Example 1 uses the momentum gradient descent algorithm to train the BP network.
Example 2 uses the Bayesian regularization algorithm to improve the generalization ability of BP network. In this example, we use two training methods, the LM optimization algorithm (trainlm) and the Bayesian regularization algorithm (trainbr), to train the BP network to fit a sine sample with white noise data.
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Size: 31744 |
Author: 李晓霜 |
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Description: BP神经网络的主程序，已经调试成功。其中传递函数可以自己随意选用，sigmoid，pureline等函数。训练函数也可以自己设置，trainlm，trainbr等等(Back propagation neural network.)
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Size: 1024 |
Author: 李宁227 |
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