\section{Class List}
Here are the classes, structs, unions and interfaces with brief descriptions:\begin{CompactList}
\item\contentsline{section}{{\bf ARX} (Linear Autoregressive model with Gaussian noise )}{\pageref{classARX}}{}
\item\contentsline{section}{{\bf Attribute} (User Info base class )}{\pageref{classAttribute}}{}
\item\contentsline{section}{{\bf bilinfn} (Class representing function $f(x,u) = Ax+Bu$ )}{\pageref{classbilinfn}}{}
\item\contentsline{section}{{\bf BM} (Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities )}{\pageref{classBM}}{}
\item\contentsline{section}{{\bf BMcond} (Conditional Bayesian Filter )}{\pageref{classBMcond}}{}
\item\contentsline{section}{{\bf CarUI} (User info for strings )}{\pageref{classCarUI}}{}
\item\contentsline{section}{{\bf chmat} (Symmetric matrix stored in square root decomposition using upper cholesky )}{\pageref{classchmat}}{}
\item\contentsline{section}{{\bf constfn} (Class representing function $f(x) = a$, here {\tt rv} is empty )}{\pageref{classconstfn}}{}
\item\contentsline{section}{{\bf diffbifn} (Class representing a differentiable function of two variables $f(x,u)$ )}{\pageref{classdiffbifn}}{}
\item\contentsline{section}{{\bf dirfilelog} (Logging into dirfile with buffer in memory )}{\pageref{classdirfilelog}}{}
\item\contentsline{section}{{\bf DoubleAttribute} (Class encapsulating all the necessary stuff to work with the double attribute )}{\pageref{classDoubleAttribute}}{}
\item\contentsline{section}{{\bf DS} (Abstract class for discrete-time sources of data )}{\pageref{classDS}}{}
\item\contentsline{section}{{\bf eEF} (General conjugate exponential family posterior density )}{\pageref{classeEF}}{}
\item\contentsline{section}{{\bf eEmp} (Weighted empirical density )}{\pageref{classeEmp}}{}
\item\contentsline{section}{{\bf egamma} (Gamma posterior density )}{\pageref{classegamma}}{}
\item\contentsline{section}{{\bf egiw} (Gauss-inverse-Wishart density stored in LD form )}{\pageref{classegiw}}{}
\item\contentsline{section}{{\bf EKF$<$ sq\_\-T $>$} (Extended \doxyref{Kalman}{p.}{classKalman} Filter )}{\pageref{classEKF}}{}
\item\contentsline{section}{{\bf EKF\_\-unQ} (Extended \doxyref{Kalman}{p.}{classKalman} filter with unknown {\tt Q} )}{\pageref{classEKF__unQ}}{}
\item\contentsline{section}{{\bf EKFCh} (Extended \doxyref{Kalman}{p.}{classKalman} Filter in Square root )}{\pageref{classEKFCh}}{}
\item\contentsline{section}{{\bf EKFfixed} (Extended \doxyref{Kalman}{p.}{classKalman} Filter with full matrices in fixed point arithmetic )}{\pageref{classEKFfixed}}{}
\item\contentsline{section}{{\bf EKFful\_\-unQR} (Extended \doxyref{Kalman}{p.}{classKalman} filter with unknown {\tt Q} and {\tt R} )}{\pageref{classEKFful__unQR}}{}
\item\contentsline{section}{{\bf EKFfull} (Extended \doxyref{Kalman}{p.}{classKalman} Filter in full matrices )}{\pageref{classEKFfull}}{}
\item\contentsline{section}{{\bf emix} (Mixture of epdfs )}{\pageref{classemix}}{}
\item\contentsline{section}{{\bf EngineUI} (User info for strings )}{\pageref{classEngineUI}}{}
\item\contentsline{section}{{\bf enorm$<$ sq\_\-T $>$} (Gaussian density with positive definite (decomposed) covariance matrix )}{\pageref{classenorm}}{}
\item\contentsline{section}{{\bf epdf} (Probability density function with numerical statistics, e.g. posterior density )}{\pageref{classepdf}}{}
\item\contentsline{section}{{\bf eprod} (Chain rule decomposition of \doxyref{epdf}{p.}{classepdf} )}{\pageref{classeprod}}{}
\item\contentsline{section}{{\bf euni} (Uniform distributed density on a rectangular support )}{\pageref{classeuni}}{}
\item\contentsline{section}{{\bf fnc} (Class representing function $f(x)$ of variable $x$ represented by {\tt rv} )}{\pageref{classfnc}}{}
\item\contentsline{section}{{\bf fsqmat} (Fake \doxyref{sqmat}{p.}{classsqmat}. This class maps \doxyref{sqmat}{p.}{classsqmat} operations to operations on full matrix )}{\pageref{classfsqmat}}{}
\item\contentsline{section}{{\bf itpp::Gamma\_\-RNG} (Gamma distribution )}{\pageref{classitpp_1_1Gamma__RNG}}{}
\item\contentsline{section}{{\bf GlobalXercesConnector} (Xerces interface class )}{\pageref{classGlobalXercesConnector}}{}
\item\contentsline{section}{{\bf IMpmsm} (State evolution model for a PMSM drive and its derivative with respect to $x$\$ )}{\pageref{classIMpmsm}}{}
\item\contentsline{section}{{\bf IMpmsmStat} (State evolution model for a PMSM drive and its derivative with respect to $x$, equation for $\omega$ is omitted.\$ )}{\pageref{classIMpmsmStat}}{}
\item\contentsline{section}{{\bf IntAttribute} (Class encapsulating all the necessary stuff to work with an int attribute )}{\pageref{classIntAttribute}}{}
\item\contentsline{section}{{\bf Kalman$<$ sq\_\-T $>$} (\doxyref{Kalman}{p.}{classKalman} filter with covariance matrices in square root form )}{\pageref{classKalman}}{}
\item\contentsline{section}{{\bf KalmanCh} (\doxyref{Kalman}{p.}{classKalman} filter in square root form )}{\pageref{classKalmanCh}}{}
\item\contentsline{section}{{\bf KalmanFull} (Basic \doxyref{Kalman}{p.}{classKalman} filter with full matrices (education purpose only)! Will be deleted soon! )}{\pageref{classKalmanFull}}{}
\item\contentsline{section}{{\bf KFcondQR} (\doxyref{Kalman}{p.}{classKalman} Filter with conditional diagonal matrices R and Q )}{\pageref{classKFcondQR}}{}
\item\contentsline{section}{{\bf KFcondR} (\doxyref{Kalman}{p.}{classKalman} Filter with conditional diagonal matrices R and Q )}{\pageref{classKFcondR}}{}
\item\contentsline{section}{{\bf ldmat} (Matrix stored in LD form, (typically known as UD) )}{\pageref{classldmat}}{}
\item\contentsline{section}{{\bf linfn} (Class representing function $f(x) = Ax+B$ )}{\pageref{classlinfn}}{}
\item\contentsline{section}{{\bf logger} (Class for storing results (and semi-results) of an experiment )}{\pageref{classlogger}}{}
\item\contentsline{section}{{\bf mEF} (Exponential family model )}{\pageref{classmEF}}{}
\item\contentsline{section}{{\bf MemDS} (Class representing off-line data stored in memory )}{\pageref{classMemDS}}{}
\item\contentsline{section}{{\bf memlog} (Logging into matrices in data format in memory )}{\pageref{classmemlog}}{}
\item\contentsline{section}{{\bf mepdf} (Unconditional \doxyref{mpdf}{p.}{classmpdf}, allows using \doxyref{epdf}{p.}{classepdf} in the role of \doxyref{mpdf}{p.}{classmpdf} )}{\pageref{classmepdf}}{}
\item\contentsline{section}{{\bf mgamma} (Gamma random walk )}{\pageref{classmgamma}}{}
\item\contentsline{section}{{\bf mgamma\_\-fix} (Gamma random walk around a fixed point )}{\pageref{classmgamma__fix}}{}
\item\contentsline{section}{{\bf mlnorm$<$ sq\_\-T $>$} (Normal distributed linear function with linear function of mean value; )}{\pageref{classmlnorm}}{}
\item\contentsline{section}{{\bf mmix} (Mixture of mpdfs with constant weights )}{\pageref{classmmix}}{}
\item\contentsline{section}{{\bf mpdf} (Conditional probability density, e.g. modeling some dependencies )}{\pageref{classmpdf}}{}
\item\contentsline{section}{{\bf MPF$<$ BM\_\-T $>$} (Marginalized Particle filter )}{\pageref{classMPF}}{}
\item\contentsline{section}{{\bf OMpmsm} (Observation model for PMSM drive and its derivative with respect to $x$ )}{\pageref{classOMpmsm}}{}
\item\contentsline{section}{{\bf PF} (Trivial particle filter with proposal density equal to parameter evolution model )}{\pageref{classPF}}{}
\item\contentsline{section}{{\bf RV} (Class representing variables, most often random variables )}{\pageref{classRV}}{}
\item\contentsline{section}{{\bf sqmat} (Virtual class for representation of double symmetric matrices in square-root form )}{\pageref{classsqmat}}{}
\item\contentsline{section}{{\bf StringAttribute} (Class encapsulating all the necessary stuff to work with a string attribute )}{\pageref{classStringAttribute}}{}
\item\contentsline{section}{{\bf UserInfo$<$ T $>$} (The main user info template class )}{\pageref{classUserInfo}}{}
\item\contentsline{section}{{\bf UserInfoCore} (\doxyref{UserInfoCore}{p.}{classUserInfoCore} class is for internal purposes only. Use UserInfo$<$T$>$ instead )}{\pageref{classUserInfoCore}}{}
\end{CompactList}
