Stability of the Decoupled Extended Kalman Filter Learning Algorithm in LSTM-Based Online Learning

We investigate the convergence and stability properties of the decoupled extended Kalman filter learning algorithm (DEKF) within the long-short term memory network (LSTM) based online learning framework. For this purpose, we model DEKF as a perturbed extended Kalman filter and derive sufficient conditions for its stability during LSTM training... (read more)

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METHOD TYPE
Sigmoid Activation
Activation Functions
Tanh Activation
Activation Functions
Memory Network
Working Memory Models
LSTM
Recurrent Neural Networks