Package | Description |
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org.hipparchus.filtering.kalman |
Kalman filter.
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org.hipparchus.filtering.kalman.extended |
Kalman filter implementation for non-linear processes.
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org.hipparchus.filtering.kalman.linear |
Kalman filter implementation for linear processes.
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org.hipparchus.linear |
Linear algebra support.
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org.hipparchus.optim.nonlinear.vector.leastsquares |
This package provides algorithms that minimize the residuals
between observations and model values.
|
Constructor and Description |
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AbstractKalmanFilter(MatrixDecomposer decomposer,
ProcessEstimate initialState)
Simple constructor.
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Constructor and Description |
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ExtendedKalmanFilter(MatrixDecomposer decomposer,
NonLinearProcess<T> process,
ProcessEstimate initialState)
Simple constructor.
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Constructor and Description |
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LinearKalmanFilter(MatrixDecomposer decomposer,
LinearProcess<T> process,
ProcessEstimate initialState)
Simple constructor.
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Modifier and Type | Class and Description |
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class |
CholeskyDecomposer
Matrix decomposer using Cholseky decomposition.
|
class |
LUDecomposer
Matrix decomposer using LU-decomposition.
|
class |
QRDecomposer
Matrix decomposer using QR-decomposition.
|
class |
SingularValueDecomposer
Matrix decomposer using Singular Value Decomposition.
|
Modifier and Type | Method and Description |
---|---|
MatrixDecomposer |
GaussNewtonOptimizer.getDecomposer()
Get the matrix decomposition algorithm.
|
MatrixDecomposer |
SequentialGaussNewtonOptimizer.getDecomposer()
Get the matrix decomposition algorithm.
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Modifier and Type | Method and Description |
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GaussNewtonOptimizer |
GaussNewtonOptimizer.withDecomposer(MatrixDecomposer newDecomposer)
Configure the matrix decomposition algorithm.
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SequentialGaussNewtonOptimizer |
SequentialGaussNewtonOptimizer.withDecomposer(MatrixDecomposer newDecomposer)
Configure the matrix decomposition algorithm.
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Constructor and Description |
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GaussNewtonOptimizer(MatrixDecomposer decomposer,
boolean formNormalEquations)
Create a Gauss Newton optimizer that uses the given matrix decomposition algorithm
to solve the normal equations.
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SequentialGaussNewtonOptimizer(MatrixDecomposer decomposer,
boolean formNormalEquations,
LeastSquaresProblem.Evaluation evaluation)
Create a sequential Gauss Newton optimizer that uses the given matrix
decomposition algorithm to solve the normal equations.
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