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long short-term memory

时间: 2023-04-28 22:06:05 浏览: 159

Long Short-term Memory

Long short-term memory (LSTM) is a recurrent neural network (RNN) architecture that remembers values over arbitrary intervals. Stored values are not modified as learning proceeds. RNNs allow forward and backward connections between neurons. An LSTM is well-suited to classify, process and predict time series given time lags of unknown size and duration between important events. Relative insensitivity to gap length gives an advantage to LSTM over alternative RNNs, hidden Markov models and other sequence learning methods in numerous applications.

Long Short-Term Memory（LSTM）是一种循环神经网络（RNN）的技术，用于处理和预测时间序列中的长期依赖关系。它通过引入记忆细胞，门控制和遗忘门来解决传统RNN的梯度消失和爆炸问题，并且能够在序列中存储和提取长期依赖信息。LSTM在许多领域，如自然语言处理、语音识别和文本生成中有着广泛的应用。

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