[{"title":"( 40 个子文件 32.44MB ) 基于matlab的CNN-LSTM深度学习网络训练,+含代码操作演示视频","children":[{"title":"1基于matlab的CNN-LSTM深度学习网络训练,有用的特征从CNN层中提取,然后反馈到LSTM层,该层形成预测的上下文顺序","children":[{"title":"re.mat <span style='color:#111;'> 4.54KB </span>","children":null,"spread":false},{"title":"train_y.txt <span style='color:#111;'> 1.91MB </span>","children":null,"spread":false},{"title":"pred.mat <span style='color:#111;'> 11.57KB </span>","children":null,"spread":false},{"title":"func","children":[{"title":"gate_ff.m <span style='color:#111;'> 204B </span>","children":null,"spread":false},{"title":"tanh_ff.m <span style='color:#111;'> 198B </span>","children":null,"spread":false},{"title":"tanh_ln.m <span style='color:#111;'> 78B </span>","children":null,"spread":false},{"title":"adam.m <span style='color:#111;'> 1.81KB </span>","children":null,"spread":false},{"title":"backprop.m <span style='color:#111;'> 373B </span>","children":null,"spread":false},{"title":"cnn_lstm_bp.m <span style='color:#111;'> 3.41KB </span>","children":null,"spread":false},{"title":"net_ff.m <span style='color:#111;'> 3.42KB </span>","children":null,"spread":false},{"title":"error_multiclass.m <span style='color:#111;'> 556B </span>","children":null,"spread":false},{"title":"train_cnn_lstm.m <span style='color:#111;'> 2.35KB </span>","children":null,"spread":false},{"title":"PrepareData_Char_LSTM.m <span style='color:#111;'> 700B </span>","children":null,"spread":false},{"title":"rotate_data.m <span style='color:#111;'> 940B </span>","children":null,"spread":false},{"title":"net_bp.m <span style='color:#111;'> 3.45KB </span>","children":null,"spread":false},{"title":"cnnConvolve.m <span style='color:#111;'> 3.30KB </span>","children":null,"spread":false},{"title":"net_init_char_lstm.m <span style='color:#111;'> 697B </span>","children":null,"spread":false},{"title":"softmaxlogloss.m <span style='color:#111;'> 605B </span>","children":null,"spread":false},{"title":"input_ff.m <span style='color:#111;'> 246B </span>","children":null,"spread":false},{"title":"soft_ff.m <span style='color:#111;'> 406B </span>","children":null,"spread":false},{"title":"soft_bp.m <span style='color:#111;'> 384B </span>","children":null,"spread":false},{"title":"average_gradients.m <span style='color:#111;'> 647B </span>","children":null,"spread":false},{"title":"test_lstm.m <span style='color:#111;'> 1.46KB </span>","children":null,"spread":false},{"title":"Copy_of_lstm_bp.m <span style='color:#111;'> 2.12KB </span>","children":null,"spread":false},{"title":"concat_data.m <span style='color:#111;'> 399B </span>","children":null,"spread":false},{"title":"hidden_bp.m <span style='color:#111;'> 138B </span>","children":null,"spread":false},{"title":"input_bp.m <span style='color:#111;'> 260B </span>","children":null,"spread":false},{"title":"cnnnet_init.m <span style='color:#111;'> 498B </span>","children":null,"spread":false},{"title":"gate_bp.m <span style='color:#111;'> 225B </span>","children":null,"spread":false},{"title":"sigmoid_ln.m <span style='color:#111;'> 104B </span>","children":null,"spread":false},{"title":"softloglossbp.m <span style='color:#111;'> 305B </span>","children":null,"spread":false},{"title":"cnn_lstm_ff.m <span style='color:#111;'> 2.69KB </span>","children":null,"spread":false}],"spread":false},{"title":"example.mat <span style='color:#111;'> 15.54MB </span>","children":null,"spread":false},{"title":"操作录像0002.avi <span style='color:#111;'> 81.70MB </span>","children":null,"spread":false},{"title":"presentation.mat <span style='color:#111;'> 15.49MB </span>","children":null,"spread":false},{"title":"Runme_cnn_lstm.m <span style='color:#111;'> 2.16KB </span>","children":null,"spread":false},{"title":"dict.txt <span style='color:#111;'> 147B </span>","children":null,"spread":false},{"title":"test_x.txt <span style='color:#111;'> 1.07MB </span>","children":null,"spread":false},{"title":"test_y.txt <span style='color:#111;'> 1.07MB </span>","children":null,"spread":false},{"title":"train_x.txt <span style='color:#111;'> 1.91MB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]