Class List

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

[detail level 123]

ekf	Extended Kalman Filter in the case of additive noise, the notations follow Van Der Merwe, phD, p. 36
ekf_param	Structure holding the parameters of the statistical linearization
ekf_state
EvolutionNoise	Mother class from which the evolution noises inherit
EvolutionAnneal	Annealing type evolution noise
EvolutionRLS	Forgetting type evolution noise
EvolutionRobbinsMonro	Robbins-Monro evolution noise
ukf	In this section we implement the Unscented Kalman Filter for parameter estimation and Joint UKF involving the Scaled Unscented Transform detailed in Van der Merwe PhD Thesis
math
parameter	UKF for parameter estimation. The notations follow "Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models",p93, PhD, van Der Merwe
ukf_param	Structure holding the parameters of the Unscented Kalman Filter
ukf_scalar_state	Pointer to the function to approximate in the scalar case
ukf_state	Structure holding the matrices manipulated by the unscented kalman filter in the vectorial case, for Parameter estimation
EvolutionNoise	Mother class from which the evolution noises inherit
EvolutionAnneal	Annealing type evolution noise
EvolutionRLS	Forgetting type evolution noise
EvolutionRobbinsMonro	Robbins-Monro evolution noise
samples
RandomSample_1D	Generate 1D samples according to a uniform distribution :
RandomSample_2D	Generate 2D samples according to a uniform distribution and put them alternativaly at the odd/even positions
RandomSample_3D	Generate 3D samples according to a uniform distribution and put them alternativaly at the odd/even positions
MaximumIndexes_1D	Extract the indexes of the nb_samples highest values of a vector Be carefull, this function is extracting the indexes as, the way it is used, it doesn't not to which sample a vector index corresponds
MaximumIndexes_2D	Extract the indexes of the nb_samples highest values of a matrix Be carefull, this function is extracting the indexes as, the way it is used, it doesn't not to which sample a vector index corresponds
DistributionSample_1D	Generate 1D samples according to a discrete vectorial distribution
DistributionSample_2D	Generate 2D samples according to a discrete matricial distribution
srstate	MUST NOT BE USED !!!!!!! Square root UKF for state estimation, additive noise case The notations follow "Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models",p115, PhD, van Der Merwe
ukf_param	Structure holding the parameters of the statistical linearization
ukf_state	Structure holding the matrices manipulated by the statistical linearization in the vectorial case for state estimation
state	UKF for state estimation, additive noise case The notations follow "Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models",p108, PhD, van Der Merwe
ukf_param	Structure holding the parameters of the statistical linearization
ukf_state	Structure holding the matrices manipulated by the statistical linearization in the vectorial case for state estimation
EvolutionNoise	Mother class from which the evolution noises inherit
EvolutionAnneal	Annealing type evolution noise
EvolutionRLS	Forgetting type evolution noise
EvolutionRobbinsMonro	Robbins-Monro evolution noise