tensorflow_probability/python/distributions/linear_gaussian_ssm.py
def kalman_transition(filtered_mean, filtered_cov,
                      transition_matrix, transition_noise):
  """Propagate a filtered distribution through a transition model."""

  predicted_mean = _propagate_mean(filtered_mean,
                                   transition_matrix,
                                   transition_noise)
  predicted_cov = _propagate_cov(filtered_cov,
                                 transition_matrix,
                                 transition_noise)
  return predicted_mean, predicted_cov
def kalman_transition(filtered_mean, filtered_cov,
                      transition_matrix, transition_noise):
  predicted_mean = _propagate_mean(filtered_mean,
                                   transition_matrix,
                                   transition_noise)
  predicted_cov = _propagate_cov(filtered_cov,
                                 transition_matrix,
                                 transition_noise)
  return predicted_mean, predicted_cov
def kalman_transition ( filtered_mean , filtered_cov , transition_matrix , transition_noise ) : predicted_mean = _propagate_mean ( filtered_mean , transition_matrix , transition_noise ) predicted_cov = _propagate_cov ( filtered_cov , transition_matrix , transition_noise ) return predicted_mean , predicted_cov
Propagate a filtered distribution through a transition model.
Propagate a filtered distribution through a transition model .