长短时记忆时间网络

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长短时记忆时间网络

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The long short-term memory (LSTM) network is a type of recurrent neural network (RNN) that is capable of learning long-term dependencies. It is designed to avoid the vanishing gradient problem that can be encountered when training traditional RNNs. The LSTM architecture includes a memory cell, an input gate, an output gate, and a forget gate, which work together to allow the network to selectively remember or forget information over time. These features make the LSTM network particularly useful in applications such as speech recognition, language translation, and video analysis.