This operator uses a Kalman Filter to produce a statistically optimal estimate of the underlying system state.
out = KALMAN({ ATTRIBUTES = ['x'], TRANSITION = '[1.0]', PROCESSNOISE = '[2.0]', MEASUREMENT = '[1.0]', MEASUREMENTNOISE = '[4.0]'}, in) |
out = 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]'}, in) |