This operator uses a kalman filter to estimate the distribution of one or more attribute values.
Parameter
- Attributes: The attributes to perform the filter on
- Transition: The transition matrix
- ProcessNoise: The process noise matrix
- Measurement: The measurement matrix
- MeasurementNoise: The measurement noise matrix
- InitialState: The initial state vector (optional)
- InitialError: The initial error matrix (optional)
- Control: The control matrix (optional)
Example
out = KALMAN({ ATTRIBUTES = ['x'], TRANSITION = '[1.0]', PROCESSNOISE = '[2.0]', MEASUREMENT = '[1.0]', MEASUREMENTNOISE = '[4.0]'}, in)
in = KALMAN({ ATTRIBUTES = ['x1','x2'], INITIALSTATE = '[0.0, 0.0, 0.0, 0.0]', INITIALERROR = '[1.0,0.0,0.0,0.0;0.0,1.0,0.0,0.0;0.0,0.0,1.0,0.0;0.0,0.0,0.0,1.0]', TRANSITION = '[1.0,0.0,1.0,0.0;0.0,1.0,0.0,1.0;0.0,0.0,1.0,0.0;0.0,0.0,0.0,1.0]', PROCESSNOISE = '[1/4, 1/4, 1/2, 1/2;1/4, 1/4, 1/2, 1/2; 1/2, 1/2, 1, 1; 1/2, 1/2, 1, 1]', MEASUREMENT = '[0.0,0.0,1.0,0.0;0.0,0.0,0.0,1.0]', MEASUREMENTNOISE = '[10.0,0.0;0.0,10.0]'}, out)