#ifndef _BAYES_FILTER_INFORMATION_ROOT#define _BAYES_FILTER_INFORMATION_ROOT/* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2002 Michael Stevens * See accompanying Bayes++.htm for terms and conditions of use. * * $Header: /cvsroot/bayesclasses/Bayes++/BayesFilter/infRtFlt.hpp,v 1.6.2.2 2004/07/18 18:38:04 mistevens Exp $ * $NoKeywords: $ *//* * Information Root Filter Scheme. *  A extended 'Square-root' Information filter as an Abstract class * * Algorithm: Square-root information propogation using QR factorisation * Ref:	P. Dyer and S. McReynolds, "Extension of Square-Root Filtering to Include Process Noise", * [1] Journal of Optimization Theory and Applications, Vol.3 No.6 1969 * Filter maintains r,R where *   inv(R)*inv(R)' = X *   r = R*x *   R is upper triangular but not strictly a Cholesky factor as diagonal may be negative * Observe algorithm has been extended to include linearised models * Discontinous observe models require that state is normailised with respect to the observation. * * The filter is operated by performing a *  predict, observe * cycle defined by the base class */#include "bayesFlt.hpp"/* Filter namespace */namespace Bayesian_filter{class Information_root_scheme : public Extended_kalman_filter{public:	FM::Vec r;			// Information Root state	FM::UTriMatrix R;	// Information Root	Information_root_scheme (std::size_t x_size, std::size_t z_initialsize = 0);	void init ();	void update ();	// Covariance form state interface	Float predict (Linrz_predict_model& f, const FM::ColMatrix& invFx, bool linear_r);	/* Generialised form, using precomputed inverse of f.Fx */	Float predict (Linrz_predict_model& f);	/* Use linrz form for r, computes inverse model using inverse_Fx */	Float predict (Linear_predict_model& f);	/* Use linear form for r, computes inverse model using inverse_Fx */	Float predict (Linear_invertable_predict_model& f)	/* Use linear form for r, and use inv.Fx from invertable model */	{		return predict(f, f.inv.Fx, true);	}	Float observe_innovation (Linrz_uncorrelated_observe_model& h, const FM::Vec& s);	Float observe_innovation (Linrz_correlated_observe_model& h, const FM::Vec& s);	// Extended_kalman_filter observe	static void inverse_Fx (FM::DenseColMatrix& invFx, const FM::Matrix& Fx);	/* Numerical Inversion of Fx using LU factorisation */};/* * Information Root Filter Scheme with exposed information state * Augments Information_root_filter with y,Y in the interface */class Information_root_info_scheme : public Information_root_scheme, virtual public Information_state_filter{public:	Information_root_info_scheme (std::size_t x_size, std::size_t z_initialsize = 0);	void init_yY ();	void update_yY ();	// Information form state interface};}//namespace#endif