org.apache.commons.math3.filter
Interface ProcessModel

All Known Implementing Classes:

DefaultProcessModel

public interface ProcessModel

Defines the process dynamics model for the use with a KalmanFilter.

Since:

3.0

Version:

$Id: ProcessModel.java 7721 2013-02-14 14:07:13Z CardosoP $

Method Summary

RealMatrix	getControlMatrix() Returns the control matrix.
RealMatrix	getInitialErrorCovariance() Returns the initial error covariance matrix.
RealVector	getInitialStateEstimate() Returns the initial state estimation vector.
RealMatrix	getProcessNoise() Returns the process noise matrix.
RealMatrix	getStateTransitionMatrix() Returns the state transition matrix.

Method Detail

getStateTransitionMatrix

RealMatrix getStateTransitionMatrix()

Returns the state transition matrix.

Returns:

the state transition matrix

getControlMatrix

RealMatrix getControlMatrix()

Returns the control matrix.

Returns:

the control matrix

getProcessNoise

RealMatrix getProcessNoise()

Returns the process noise matrix. This method is called by the KalmanFilter every prediction step, so implementations of this interface may return a modified process noise depending on the current iteration step.

Returns:

the process noise matrix

See Also:

KalmanFilter.predict(), KalmanFilter.predict(double[]), KalmanFilter.predict(RealVector)

getInitialStateEstimate

RealVector getInitialStateEstimate()

Returns the initial state estimation vector.

Note: if the return value is zero, the Kalman filter will initialize the state estimation with a zero vector.

Returns:

the initial state estimation vector

getInitialErrorCovariance

RealMatrix getInitialErrorCovariance()

Returns the initial error covariance matrix.

Note: if the return value is zero, the Kalman filter will initialize the error covariance with the process noise matrix.

Returns:

the initial error covariance matrix