Support a batch of sequences being processed simultaneously, leading to dramatic efficiency improvement.
KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics
This branch simulates architecture #2 in our paper. There are main files simulating the linear and non-linear cases respectively.
- Linear case (canonical model or constant acceleration model)
python3 main_linear_canonical.py
python3 main_linear_CA.py
- Non-linear Lorenz Attractor case (Discrete-Time, decimation, or Non-linear observation function)
python3 main_lor_DT.py
python3 main_lor_decimation.py
python3 main_lor_DT_NLobs.py
- Simulations/model_name/parameters.py
Contain model settings: m, n, f/F, h/H, Q and R.
- Simulations/config.py
Contain dataset size, training parameters and network settings.
- main files
Set flags, paths, etc.