LSTM classifiers require larger noise statistic separations than model-based EM classifiers to achieve reliable binary time series classification and saturate below the optimal Kalman filter reference when models differ only in measurement noise.
Deep learning for time series classification: a review,
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An Objective Performance Evaluation of the LSTM Networks in Time Series Classification
LSTM classifiers require larger noise statistic separations than model-based EM classifiers to achieve reliable binary time series classification and saturate below the optimal Kalman filter reference when models differ only in measurement noise.