def METHOD_NAME(z, R, H):
  """
  Fuse measurement distribution into state distribution, given a linear mapping
  from state space to measurement space.
  input:
    z: row vector of sensorization measurements (1 x I)
    R: sensorization noise covariance matrix (I x I)
    H: matrix mapping from state space to measurement space (I x S)
  output:
    - the mean of the system state distribution (1 x S)
    - the covariance of the system state distribution (S x S)
  """
  # precompute common product
  RiH = np.dot(np.linalg.inv(R), H)
  # return the system state distribution
  P = np.linalg.inv(np.dot(H.T, RiH))
  x = np.dot(np.dot(z, RiH), P)
  return (x, P)