Apache Commons Math 3.6.1 · org.apache.commons.math3.filter.ProcessModel

Method Summary

Modifier and Type	Method and Description
public RealMatrix	Returns: the control matrix getControlMatrix() Returns the control matrix.
public RealMatrix	Returns: the initial error covariance matrix getInitialErrorCovariance() Returns the initial error covariance matrix.
public RealVector	Returns: the initial state estimation vector getInitialStateEstimate() Returns the initial state estimation vector.
public RealMatrix	Returns: the process noise matrix getProcessNoise() Returns the process noise matrix.
public RealMatrix	Returns: the state transition matrix getStateTransitionMatrix() Returns the state transition matrix.

Method Detail

getControlMatrix	back to summary
public RealMatrix getControlMatrix() Returns the control matrix. Returns:RealMatrix the control matrix

getControlMatrix

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public RealMatrix getControlMatrix()

Returns the control matrix.

Returns:RealMatrix: the control matrix

getInitialErrorCovariance	back to summary
public 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:RealMatrix the initial error covariance matrix

getInitialErrorCovariance

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public 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:RealMatrix: the initial error covariance matrix

getInitialStateEstimate	back to summary
public 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:RealVector the initial state estimation vector

getInitialStateEstimate

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public 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:RealVector: the initial state estimation vector

getProcessNoise back to summary

getProcessNoise	back to summary
public 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:RealMatrix the process noise matrix See Also `KalmanFilter#predict()`, `KalmanFilter#predict(double[])`, `KalmanFilter#predict(RealVector)`

public 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:RealMatrix: the process noise matrix
See Also: KalmanFilter#predict(), KalmanFilter#predict(double[]), KalmanFilter#predict(RealVector)

getStateTransitionMatrix	back to summary
public RealMatrix getStateTransitionMatrix() Returns the state transition matrix. Returns:RealMatrix the state transition matrix

getStateTransitionMatrix

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public RealMatrix getStateTransitionMatrix()

Returns the state transition matrix.

Returns:RealMatrix: the state transition matrix

public Interface ProcessModel

Method Summary

Method Detail