predict
Estimates subsequent model state without control parameters.
Return
estimated state.
See also
Throws
Signal
if something fails.
Estimates subsequent model state. The function estimates the subsequent stochastic model state by its current state and stores it at statePre:
x'<sub>k</sub>=A*x<sub>k</sub>+B*u<sub>k</sub>
P'<sub>k</sub>=A*P<sub>k-1</sub>*A<sup>T</sup> + Q,
where
x'<sub>k</sub> is predicted state (statePre),
x<sub>k-1</sub> is corrected state on the previous step (statePost)
(should be initialized somehow in the beginning, zero vector by
default),
u<sub>k</sub> is external control (<code>control</code> parameter),
P'<sub>k</sub> is prior error covariance matrix (error_cov_pre)
P<sub>k-1</sub> is posteriori error covariance matrix on the previous
step (error_cov_post)
(should be initialized somehow in the beginning, identity matrix by
default),
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Return
estimated state as a 1 column matrix having dp rows (where dp = number of dynamic parameters).
Parameters
control
control vector (uk), should be null if there is no external control (controlParams=0). If provided and filter uses control parameters, it must be a 1 column matrix having cp rows (where cp = number of control parameters), otherwise a SignalProcessingException will be raised.
Throws
Signal
if something fails.