Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

[detail level 12]

▼NBFL
CAnalyticConditionalGaussian	Abstract Class representing all FULL Analytical Conditional gaussians
CAnalyticConditionalGaussianAdditiveNoise	Abstract Class representing all full Analytical Conditional gaussians with Additive Gaussian Noise
CAnalyticMeasurementModelGaussianUncertainty
CAnalyticSystemModelGaussianUncertainty	Class for analytic system models with additive Gauss. uncertainty
CASIRFilter	ASIR: Auxiliary Particle Filter
CBackwardFilter	Virtual Baseclass representing all bayesian backward filters
CBootstrapFilter	Particular particle filter : Proposal PDF = SystemPDF
CConditionalGaussian	Abstract Class representing all Conditional gaussians
CConditionalGaussianAdditiveNoise	Abstract Class representing all Conditional Gaussians with additive gaussian noise
CConditionalPdf	Abstract Class representing conditional Pdfs P(x | ...)
CDiscreteConditionalPdf	Class representing all FULLY Discrete Conditional PDF's
CDiscretePdf	Class representing a PDF on a discrete variable
CDiscreteSystemModel	Class for discrete System Models
CEKFProposalDensity	Proposal Density for non-linear systems with additive Gaussian Noise (using a EKF Filter)
CEKParticleFilter	Particle filter using EKF for proposal step
CExtendedKalmanFilter
CFilter	Abstract class representing an interface for Bayesian Filters
CFilterProposalDensity	Proposal Density for non-linear systems with additive Gaussian Noise (using a (analytic) Filter)
CGaussian	Class representing Gaussian (or normal density)
CHistogramFilter	Class representing the histogram filter
CInnovationCheck	Class implementing an innovationCheck used in IEKF
CIteratedExtendedKalmanFilter
CKalmanFilter	Class representing the family of all Kalman Filters (EKF, IEKF, ...)
CLinearAnalyticConditionalGaussian	Linear Conditional Gaussian
CLinearAnalyticMeasurementModelGaussianUncertainty	Class for linear analytic measurementmodels with additive gaussian noise
CLinearAnalyticMeasurementModelGaussianUncertainty_Implicit	Class for linear analytic measurementmodels with additive gaussian noise
CLinearAnalyticSystemModelGaussianUncertainty	Class for linear analytic systemmodels with additive gaussian noise
CMCPdf	Monte Carlo Pdf: Sample based implementation of Pdf
CMeasurementModel
CMixture	Class representing a mixture of PDFs, the mixture can contain different
CMixtureBootstrapFilter	Particular mixture particle filter : Proposal PDF = SystemPDF
CMixtureParticleFilter	Virtual Class representing all Mixture particle filters
CNonLinearAnalyticConditionalGaussian_Ginac	Conditional Gaussian for an analytic nonlinear system using Ginac:
CNonLinearAnalyticMeasurementModelGaussianUncertainty_Ginac	Class for nonlinear analytic measurementmodels with additive gaussian noise
CNonLinearAnalyticSystemModelGaussianUncertainty_Ginac	Class for nonlinear analytic systemmodels with additive gaussian noise
CNonminimalKalmanFilter
COptimalImportanceDensity	Optimal importance density for Nonlinear Gaussian SS Models
COptimalimportancefilter	Particular particle filter: Proposal PDF = Optimal Importance function
CParticleFilter	Virtual Class representing all particle filters
CParticleSmoother	Class representing a particle backward filter
CPdf	Class PDF: Virtual Base class representing Probability Density Functions
CProbability	Class representing a probability (a double between 0 and 1)
CRauchTungStriebel	Class representing all Rauch-Tung-Striebel backward filters
CSample
CSRIteratedExtendedKalmanFilter
CSystemModel
CUniform	Class representing uniform density
CWeightedSample
▼NMatrixWrapper
CColumnVector_Wrapper	Class ColumnVectorWrapper
CMatrix_Wrapper	Class Matrixwrapper
CRowVector_Wrapper	Class RowVectorWrapper
CSymmetricMatrix_Wrapper	Class SymmetricMatrixWrapper