搜索资源列表
Elman
- Elman神经网络:Elman网络是 J. L. Elman于1990年首先针对语音处理问题而提出来的, 它是一种典型的局部回归网络( global feed for ward l ocal recurrent)。Elman网络可以看作是一个具有局部记忆单元和局部反馈连接的前向神经网络。Elman网络具有与多层前向网络相似的多层结构。它的主要结构是前馈连接, 包括输入层、 隐含层、 输出层, 其连接权可以进行学习修正 反馈连接由一组“结构 ” 单元构成,用来记忆前一时刻的输出值, 其连接权值是固
caffe-recurrent-v4
- 构建神经网络,进行数据处理,包括卷积神经网络和递归神经网络-Construction of neural networks, data processing, including convolution neural networks and recurrent neural network
RNN-Tutorial-master
- 循环神经网络教程 循环神经网络教程-Recurrent Neural Network TutorialRecurrent Neural Network TutorialRecurrent Neural Network Tutorial
案例1 BP神经网络的数据分类-语音特征信号分类
- 前馈循环神经网络,用于处理语音识别,里面是matlab源代码,以及实例。学习神经网络算法很有帮助。(Feed forward recurrent neural network for speech recognition, which is the matlab source code, and an example. Learning neural network algorithms is very helpful.)
rc_matlab
- recurrent method for neural network
task3
- 使用循环神经网络实现SMPCUP2017任务3的用户活跃度预测(Predict the growth value of users via recurrent neural network in SMPCUP 2017 task 3)
RNN
- python实现的循环神经网络,带数据集,可运行(Python implemented recurrent neural network, with data sets, can be run)
LSTM_main
- LSTM(Long Short-Term Memory)是长短期记忆网络,是一种时间递归神经网络,适合于处理和预测时间序列中间隔和延迟相对较长的重要事件。(LSTM (Long Short-Term Memory) is a long and short term memory network. It is a kind of time recurrent neural network, which is suitable for dealing with and predicting impo
RNN
- 用matlab做的预测的例子,采用rnn循环神经网络实现,亲测可用(Using MATLAB to do the prediction example, using recurrent neural network RNN implementation, pro test available.)
lstm
- 循环神经网络LSTM可以预测时间序列数据,根据历史时刻的信息预测未来时刻的信息(the recurrent neural network is very useful to predict data in the future)
23_time_series_prediction
- 用 Python 机器学习,时间序列模型预测, 循环神经网络(Python Machine Learning, Time Series Model Prediction, recurrent Neural Network)
ESNtools
- 一种新型的循环神经网络(RNN),在时序预测领域有广泛应用前景(A new type of recurrent neural network (RNN) has a wide application prospect in the field of time series prediction)