【469】RNN, LSTM参考博客

参考：Illustrated Guide to Recurrent Neural Networks

参考：Illustrated Guide to LSTM’s and GRU’s: A step by step explanation

参考：Understanding LSTM Networks

参考：Recurrent Neural Networks | MIT 6.S191 —— YouTube

参考：The Unreasonable Effectiveness of Recurrent Neural Networks

参考：Anyone Can Learn To Code an LSTM-RNN in Python (Part 1: RNN)

参考：The Unreasonable Effectiveness of Recurrent Neural Networks

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RNN

feed forward

1. input1 -> hidden layer1 -> output1
2. (hidden layer1 + input2) -> hidden layer2 -> output2
3. (hidden layer2 + input3) -> hidden layer3 -> output3
4. (hidden layer3 + input4) -> hidden layer4 -> output4

back propagation（橙色是权重更新）

1. W_hy4 -> W_xh4
2. W_hy3 -> W_xh3
3. W_hy2 -> W_xh2
4. W_hy1 -> W_xh1

RNN形式

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LSTM

 

 

 

 

 

 

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