搜索资源列表
BPgaijin
- 采用动量梯度下降算法训练BP网络,有需要的下哦~-using gradient descent algorithm BP training network, it is necessary to the next, oh ~
BPnet
- 采用动量梯度下降算法训练 BP 网络。
动量梯度下降算法和贝叶斯正则化算法BP神经网络程序实例
- 动量梯度下降算法和贝叶斯正则化算法BP神经网络程序实例，可以直接运行。
ANN
- BP神经网络的matlab程序（动量梯度下降算法训练 、贝叶斯正则化算法）-BP neural network matlab program
bp.example
- 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 (t
BP_neural_network
- 采用动量梯度下降算法训练BP网络，程序后面有详细注释-Gradient descent algorithm using momentum BP network training, procedures followed have detailed notes
subb
- 利用动量梯度下降算法训练BP网络，得到误差显示图，并最终进行预测-Gradient descent algorithm using momentum BP network training, the error display map, and, ultimately, to predict
ebp1
- matlab动量梯度下降算法 生成一个新的前向神经网络 对BP神经网络进行训练 对BP神经网络进行仿真-Momentum matlab gradient descent algorithm to generate a new feed-forward neural networks trained BP neural network on the BP neural network simulation
dltd
- 采用动量梯度下降算法训练BP网络。在本源码中，训练样本定如下：p=[-1 -2 3 1 -1 1 5 -3] 目标矢量为t=[-1 -1 1 1]-Gradient descent algorithm using momentum BP network training. In this source, the training sample set as follows: p = [-1-2 3 1 -1 1 5-3] target vector for t = [-1-1 1 1]
BP1
- 采用动量梯度下降算法训练 BP 神经网络预测的一个实例分析-Gradient descent algorithm with momentum training BP neural network analysis of an instance of
shenjingwangluo
- 神经网络实例 采用动量梯度下降算法训练 BP 网络。-Neural Network Example
matlab
- 采用动量梯度下降算法训练 BP 网络训练样本定义如下： 输入矢量为 p =[-1 -2 3 1 -1 1 5 -3] 目标矢量为 t = [-1 -1 1 1]-采用动量梯度下降算法训练 BP 网络训练样本定义如下： 输入矢量为 p =[-1-2 3 1 -1 1 5-3] 目标矢量为 t = [-1-1 1 1]
DLBP
- 一种改进的BP算法，基于动量梯度的，非常经典，实际可用-An improved BP algorithm based on the momentum gradient, very classic, the actual available
TRAINGDM-to-train-BP(code)
- 采用动量梯度下降算法训练 BP 网络。 训练样本定义如下： 输入矢量为 p =[-1 -2 3 1 -1 1 5 -3] 目标矢量为 t = [-1 -1 1 1]-Use TRAINGDM to train BP network.
bp-neural
- 采用动量梯度下降算法来训练 BP 神经网络，效果很好-BP neural training
bp-neural-training
- 采用动量梯度下降算法来训练 BP 神经网络，效果很好-BP neural training
train-the-BP-network
- 采用动量梯度下降算法训练 BP 网络，输入矢量和目标矢量-Using momentum gradient descent algorithm to train the BP network
natural-gradient-algorithm
- 变步长自然梯度算法实现盲源分离，后面还有动量项自然梯度算法-Variable step-size natural gradient algorithm for blind source separation
dongliangsuanfa
- 采用动量梯度下降算法训练BP网络，证明,一个3层的BP网络能够实现任意的连续映射,可以任意精度逼近任何给定的连续函数。-Using momentum gradient descent algorithm to train the BP network, proved that a three-layer BP network to any continuous mapping can be arbitrary-precision approach any given continuous fun
BP_Differ_Train
- BP神经网络算法用来拟合加噪信号，并以动量梯度下降算法和减少内存的Levenberg-Marquardt算法两种训练方法进行该实例下的性能对比-BP neural network algorithm used to fit the noise signal, and to reduce the momentum gradient algorithm and memory Levenberg-Marquardt algorithm two training methods to compare t