Uses of Class
de.unihalle.informatik.MiToBo.math.LinearTransformGaussNoise

Packages that use LinearTransformGaussNoise

Package	Description
de.unihalle.informatik.MiToBo.tracking.multitarget.algo
de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.impl

Uses of LinearTransformGaussNoise in de.unihalle.informatik.MiToBo.tracking.multitarget.algo

Fields in de.unihalle.informatik.MiToBo.tracking.multitarget.algo declared as LinearTransformGaussNoise

Modifier and Type	Field and Description
protected LinearTransformGaussNoise[]	MultiTargetIMMFilter.predictors dynamic models
protected LinearTransformGaussNoise	MultiTargetIMMFilter.projector observation model

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.algo that return LinearTransformGaussNoise

Modifier and Type	Method and Description
protected LinearTransformGaussNoise[]	MultiObservationGenerator.createDynamicModels()
protected LinearTransformGaussNoise	MultiObservationGenerator.createObservationModel()

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.algo with parameters of type LinearTransformGaussNoise

Modifier and Type	Method and Description
protected MultiState<MotionModelID>	MultiObservationGenerator.generateNextStates(MultiState<MotionModelID> X, LinearTransformGaussNoise[] dynamicModels)
protected MultiState<MotionModelID>	MultiObservationGenerator.generateObservations(MultiState<MotionModelID> states, LinearTransformGaussNoise obsModel, MultiStateFactory<MotionModelID> obsFactory)

Constructors in de.unihalle.informatik.MiToBo.tracking.multitarget.algo with parameters of type LinearTransformGaussNoise

Constructor and Description
MultiTargetIMMFilter(Vector<GaussMixDistribution> initialStateDistrib, LinearTransformGaussNoise observationModel, LinearTransformGaussNoise[] dynamicsModels, Jama.Matrix markov, double delta_t, ExponentialDistribution targetDeathDistrib, GaussMixDistribution newbornStateDistrib, Jama.Matrix stateFromObs, AbstractMultiStateFactory<MotionModelID> factoryX, AbstractMultiStateFactory<MotionModelID> factoryZ) Constructor that initializes the internal random generator with seed 1.
MultiTargetIMMFilter(Vector<GaussMixDistribution> initialStateDistrib, LinearTransformGaussNoise observationModel, LinearTransformGaussNoise[] dynamicsModels, Jama.Matrix markov, double delta_t, ExponentialDistribution targetDeathDistrib, GaussMixDistribution newbornStateDistrib, Jama.Matrix stateFromObs, AbstractMultiStateFactory<MotionModelID> factoryX, AbstractMultiStateFactory<MotionModelID> factoryZ) Constructor that initializes the internal random generator with seed 1.
MultiTargetIMMFilter(Vector<GaussMixDistribution> initialStateDistrib, LinearTransformGaussNoise observationModel, LinearTransformGaussNoise[] dynamicsModels, Jama.Matrix markov, double delta_t, ExponentialDistribution targetDeathDistrib, GaussMixDistribution newbornStateDistrib, Jama.Matrix stateFromObs, AbstractMultiStateFactory<MotionModelID> factoryX, AbstractMultiStateFactory<MotionModelID> factoryZ, Random rand) Constructor.
MultiTargetIMMFilter(Vector<GaussMixDistribution> initialStateDistrib, LinearTransformGaussNoise observationModel, LinearTransformGaussNoise[] dynamicsModels, Jama.Matrix markov, double delta_t, ExponentialDistribution targetDeathDistrib, GaussMixDistribution newbornStateDistrib, Jama.Matrix stateFromObs, AbstractMultiStateFactory<MotionModelID> factoryX, AbstractMultiStateFactory<MotionModelID> factoryZ, Random rand) Constructor.

Uses of LinearTransformGaussNoise in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.impl

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.impl with parameters of type LinearTransformGaussNoise

Modifier and Type	Method and Description
void	MultiStateDistributionIndepGaussians.predict(LinearTransformGaussNoise predictor)
void	MultiStateDistributionIndepGaussians.predictIndep(int i, LinearTransformGaussNoise predictor)
void	MultiStateDistributionIndepGaussians.update(LinearTransformGaussNoise projector, AbstractMultiState<T> observations)
void	MultiStateDistributionIndepGaussians.updateIndep(int i, int j, LinearTransformGaussNoise projector, AbstractMultiState<T> observations) Update i-th Gaussian component with j-th observation
void	MultiStateDistributionIndepGaussians.updateIndep(int i, LinearTransformGaussNoise projector, AbstractMultiState<T> observations)