AnalyticConditionalGaussian | Abstract Class representing all _FULL_ Analytical Conditional gaussians |
AnalyticConditionalGaussianAdditiveNoise | Abstract Class representing all full Analytical Conditional gaussians with Additive Gaussian Noise |
AnalyticMeasurementModelGaussianUncertainty | |
AnalyticSystemModelGaussianUncertainty | Class for analytic system models with additive Gauss. uncertainty |
ASIRFilter< StateVar, MeasVar > | ASIR: Auxiliary Particle Filter |
BackwardFilter< StateVar > | Virtual Baseclass representing all bayesian backward filters |
BootstrapFilter< StateVar, MeasVar > | Particular particle filter : Proposal PDF = SystemPDF |
ColumnVector | Wrapper class for ColumnVectors (Boost implementation) |
ColumnVector_Wrapper | Class ColumnVectorWrapper |
ColumnVector_Wrapper | Class ColumnVectorWrapper |
ConditionalGaussian | Abstract Class representing all Conditional gaussians |
ConditionalGaussianAdditiveNoise | Abstract Class representing all Conditional Gaussians with additive gaussian noise |
ConditionalPdf< Var, CondArg > | Abstract Class representing conditional Pdfs P(x | ...) |
DiscreteConditionalPdf | Abstract Class representing all _FULLY_ Discrete Conditional PDF's |
DiscretePdf | Class representing a PDF on a discrete variable |
DiscretePdf | Class representing a PDF on a discrete variable |
DiscreteSystemModel | Class for discrete System Models |
EKFProposalDensity | Proposal Density for non-linear systems with additive Gaussian Noise (using a EKF Filter) |
EKParticleFilter | Particle filter using EKF for proposal step |
ExtendedKalmanFilter | |
Filter< StateVar, MeasVar > | Abstract class representing an interface for Bayesian Filters |
FilterProposalDensity | Proposal Density for non-linear systems with additive Gaussian Noise (using a (analytic) Filter) |
Gaussian | Class representing Gaussian (or normal density) |
HistogramFilter< MeasVar > | Class representing the histogram filter |
InnovationCheck | Class implementing an innovationCheck used in IEKF |
IteratedExtendedKalmanFilter | |
KalmanFilter | Class representing the family of all Kalman Filters (EKF, IEKF, ...) |
LinearAnalyticConditionalGaussian | Linear Conditional Gaussian |
LinearAnalyticMeasurementModelGaussianUncertainty | Class for linear analytic measurementmodels with additive gaussian noise |
LinearAnalyticMeasurementModelGaussianUncertainty_Implicit | Class for linear analytic measurementmodels with additive gaussian noise |
LinearAnalyticSystemModelGaussianUncertainty | Class for linear analytic systemmodels with additive gaussian noise |
Matrix | Implementation of Matrixwrapper using Boost |
Matrix_Wrapper | Class Matrixwrapper |
Matrix_Wrapper | Class Matrixwrapper |
MCPdf< T > | Monte Carlo Pdf: Sample based implementation of Pdf |
MCPdf< T > | Monte Carlo Pdf: Sample based implementation of Pdf |
MeasurementModel< MeasVar, StateVar > | |
Mixture< T > | Class representing a mixture of PDFs, the mixture can contain different |
Mixture< T > | Class representing a mixture of PDFs, the mixture can contain different |
MixtureBootstrapFilter< StateVar, MeasVar > | Particular mixture particle filter : Proposal PDF = SystemPDF |
MixtureParticleFilter< StateVar, MeasVar > | Virtual Class representing all Mixture particle filters |
NonLinearAnalyticConditionalGaussian_Ginac | Conditional Gaussian for an analytic nonlinear system using Ginac: |
NonLinearAnalyticMeasurementModelGaussianUncertainty_Ginac | Class for nonlinear analytic measurementmodels with additive gaussian noise |
NonLinearAnalyticSystemModelGaussianUncertainty_Ginac | Class for nonlinear analytic systemmodels with additive gaussian noise |
NonminimalKalmanFilter | |
OptimalImportanceDensity | Optimal importance density for Nonlinear Gaussian SS Models |
Optimalimportancefilter< StateVar, MeasVar > | Particular particle filter: Proposal PDF = Optimal Importance function |
ParticleFilter< StateVar, MeasVar > | Virtual Class representing all particle filters |
ParticleSmoother< StateVar > | Class representing a particle backward filter |
Pdf< T > | Class PDF: Virtual Base class representing Probability Density Functions |
Pdf< T > | Class PDF: Virtual Base class representing Probability Density Functions |
Probability | Class representing a probability (a double between 0 and 1) |
Probability | Class representing a probability (a double between 0 and 1) |
RauchTungStriebel | Class representing all Rauch-Tung-Striebel backward filters |
RowVector | Wrapper class for RowVectors (Boost implementation) |
RowVector_Wrapper | Class RowVectorWrapper |
RowVector_Wrapper | Class RowVectorWrapper |
Sample< T > | |
Sample< T > | |
SRIteratedExtendedKalmanFilter | |
SymmetricMatrix | |
SymmetricMatrix_Wrapper | Class SymmetricMatrixWrapper |
SymmetricMatrix_Wrapper | Class SymmetricMatrixWrapper |
SystemModel< T > | |
Uniform | Class representing uniform density |
WeightedSample< T > | |
WeightedSample< T > | |