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神经网络时序 | Solve a nonlinear time series problem by training a dynamic neural network |
timedelaynet | Time delay neural network |
narxnet | Nonlinear autoregressive neural network with external input |
narnet | Nonlinear autoregressive neural network |
layrecnet | Layer recurrent neural network |
distdelaynet | Distributed delay network |
train | Train shallow neural network |
gensim | Generate Simulink block for shallow neural network simulation |
adddelay | Add delay to neural network response |
removedelay | Remove delay to neural network’s response |
closeloop | Convert neural network open-loop feedback to closed loop |
openloop | Convert neural network closed-loop feedback to open loop |
ploterrhist | Plot error histogram |
plotinerrcorr | Plot input to error time-series cross-correlation |
plotregression | Plot linear regression |
plotresponse | Plot dynamic network time series response |
ploterrcorr | Plot autocorrelation of error time series |
genFunction | Generate MATLAB function for simulating shallow neural network |
使用 Neural Network Time Series 和命令行函数进行时序预测。
Design Time Series Time-Delay Neural Networks
Learn to design focused time-delay neural network (FTDNN) for time-series prediction.
Multistep Neural Network Prediction
Learn multistep neural network prediction.
创建和训练外因输入非线性自回归网络 (NARX)。
Design Layer-Recurrent Neural Networks
Create and train a dynamic network that is a Layer-Recurrent Network (LRN).
Deploy Shallow Neural Network Functions
Simulate and deploy trained shallow neural networks using MATLAB® tools.
Deploy Training of Shallow Neural Networks
Learn how to deploy training of shallow neural networks.
此示例说明 NARX(具有外部输入的非线性自回归)神经网络如何对磁悬浮动态系统建模。
使用并行和分布式计算,可以加快神经网络训练和仿真以及处理大量数据的速度。
Automatically Save Checkpoints During Neural Network Training
Save intermediate results to protect the value of long training runs.
Optimize Neural Network Training Speed and Memory
Make neural network training more efficient.
对输入和目标进行预处理,以提高训练效率。
了解如何在训练前使用 configure
函数手动配置网络。
使用函数将数据分为训练集、验证集和测试集。
不同问题类型的训练算法比较。
了解提高泛化能力和防止过拟合的方法。
Train Neural Networks with Error Weights
Learn how to use error weighting when training neural networks.
Normalize Errors of Multiple Outputs
Learn how to fit output elements with different ranges of values.
How Dynamic Neural Networks Work
Learn how feedforward and recurrent networks work.
Multiple Sequences with Dynamic Neural Networks
Manage time-series data that is available in several short sequences.
Neural Network Time-Series Utilities
Learn how to use utility functions to manipulate neural network data.
试验浅层神经网络时要使用的样本数据集列表。
了解定义网络基本特征的属性。
Neural Network Subobject Properties
Learn properties that define network details such as inputs, layers, outputs, targets, biases, and weights.