[91] | 1 | \section{Class List} |
---|
[3] | 2 | Here are the classes, structs, unions and interfaces with brief descriptions:\begin{CompactList} |
---|
[99] | 3 | \item\contentsline{section}{{\bf ARX} (Linear Autoregressive model with Gaussian noise )}{\pageref{classARX}}{} |
---|
[140] | 4 | \item\contentsline{section}{{\bf Attribute} (User Info base class )}{\pageref{classAttribute}}{} |
---|
[91] | 5 | \item\contentsline{section}{{\bf bilinfn} (Class representing function $f(x,u) = Ax+Bu$ )}{\pageref{classbilinfn}}{} |
---|
[4] | 6 | \item\contentsline{section}{{\bf BM} (Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities )}{\pageref{classBM}}{} |
---|
[32] | 7 | \item\contentsline{section}{{\bf BMcond} (Conditional Bayesian Filter )}{\pageref{classBMcond}}{} |
---|
[140] | 8 | \item\contentsline{section}{{\bf CarUI} (User info for strings )}{\pageref{classCarUI}}{} |
---|
[37] | 9 | \item\contentsline{section}{{\bf chmat} (Symmetric matrix stored in square root decomposition using upper cholesky )}{\pageref{classchmat}}{} |
---|
[91] | 10 | \item\contentsline{section}{{\bf constfn} (Class representing function $f(x) = a$, here {\tt rv} is empty )}{\pageref{classconstfn}}{} |
---|
| 11 | \item\contentsline{section}{{\bf diffbifn} (Class representing a differentiable function of two variables $f(x,u)$ )}{\pageref{classdiffbifn}}{} |
---|
| 12 | \item\contentsline{section}{{\bf dirfilelog} (Logging into dirfile with buffer in memory )}{\pageref{classdirfilelog}}{} |
---|
[140] | 13 | \item\contentsline{section}{{\bf DoubleAttribute} (Class encapsulating all the necessary stuff to work with the double attribute )}{\pageref{classDoubleAttribute}}{} |
---|
[19] | 14 | \item\contentsline{section}{{\bf DS} (Abstract class for discrete-time sources of data )}{\pageref{classDS}}{} |
---|
[8] | 15 | \item\contentsline{section}{{\bf eEF} (General conjugate exponential family posterior density )}{\pageref{classeEF}}{} |
---|
[32] | 16 | \item\contentsline{section}{{\bf eEmp} (Weighted empirical density )}{\pageref{classeEmp}}{} |
---|
| 17 | \item\contentsline{section}{{\bf egamma} (Gamma posterior density )}{\pageref{classegamma}}{} |
---|
[99] | 18 | \item\contentsline{section}{{\bf egiw} (Gauss-inverse-Wishart density stored in LD form )}{\pageref{classegiw}}{} |
---|
[22] | 19 | \item\contentsline{section}{{\bf EKF$<$ sq\_\-T $>$} (Extended \doxyref{Kalman}{p.}{classKalman} Filter )}{\pageref{classEKF}}{} |
---|
[33] | 20 | \item\contentsline{section}{{\bf EKF\_\-unQ} (Extended \doxyref{Kalman}{p.}{classKalman} filter with unknown {\tt Q} )}{\pageref{classEKF__unQ}}{} |
---|
[79] | 21 | \item\contentsline{section}{{\bf EKFCh} (Extended \doxyref{Kalman}{p.}{classKalman} Filter in Square root )}{\pageref{classEKFCh}}{} |
---|
[145] | 22 | \item\contentsline{section}{{\bf EKFfixed} (Extended \doxyref{Kalman}{p.}{classKalman} Filter with full matrices in fixed point arithmetic )}{\pageref{classEKFfixed}}{} |
---|
[140] | 23 | \item\contentsline{section}{{\bf EKFful\_\-unQR} (Extended \doxyref{Kalman}{p.}{classKalman} filter with unknown {\tt Q} and {\tt R} )}{\pageref{classEKFful__unQR}}{} |
---|
[79] | 24 | \item\contentsline{section}{{\bf EKFfull} (Extended \doxyref{Kalman}{p.}{classKalman} Filter in full matrices )}{\pageref{classEKFfull}}{} |
---|
[106] | 25 | \item\contentsline{section}{{\bf emix} (Mixture of epdfs )}{\pageref{classemix}}{} |
---|
[140] | 26 | \item\contentsline{section}{{\bf EngineUI} (User info for strings )}{\pageref{classEngineUI}}{} |
---|
[22] | 27 | \item\contentsline{section}{{\bf enorm$<$ sq\_\-T $>$} (Gaussian density with positive definite (decomposed) covariance matrix )}{\pageref{classenorm}}{} |
---|
[4] | 28 | \item\contentsline{section}{{\bf epdf} (Probability density function with numerical statistics, e.g. posterior density )}{\pageref{classepdf}}{} |
---|
[140] | 29 | \item\contentsline{section}{{\bf eprod} (Chain rule decomposition of \doxyref{epdf}{p.}{classepdf} )}{\pageref{classeprod}}{} |
---|
[32] | 30 | \item\contentsline{section}{{\bf euni} (Uniform distributed density on a rectangular support )}{\pageref{classeuni}}{} |
---|
[91] | 31 | \item\contentsline{section}{{\bf fnc} (Class representing function $f(x)$ of variable $x$ represented by {\tt rv} )}{\pageref{classfnc}}{} |
---|
[8] | 32 | \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}}{} |
---|
[32] | 33 | \item\contentsline{section}{{\bf itpp::Gamma\_\-RNG} (Gamma distribution )}{\pageref{classitpp_1_1Gamma__RNG}}{} |
---|
[140] | 34 | \item\contentsline{section}{{\bf GlobalXercesConnector} (Xerces interface class )}{\pageref{classGlobalXercesConnector}}{} |
---|
[145] | 35 | \item\contentsline{section}{{\bf IMpmsm} (State evolution model for a PMSM drive and its derivative with respect to $x$\$ )}{\pageref{classIMpmsm}}{} |
---|
| 36 | \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}}{} |
---|
[140] | 37 | \item\contentsline{section}{{\bf IntAttribute} (Class encapsulating all the necessary stuff to work with an int attribute )}{\pageref{classIntAttribute}}{} |
---|
[22] | 38 | \item\contentsline{section}{{\bf Kalman$<$ sq\_\-T $>$} (\doxyref{Kalman}{p.}{classKalman} filter with covariance matrices in square root form )}{\pageref{classKalman}}{} |
---|
[37] | 39 | \item\contentsline{section}{{\bf KalmanCh} (\doxyref{Kalman}{p.}{classKalman} filter in square root form )}{\pageref{classKalmanCh}}{} |
---|
[8] | 40 | \item\contentsline{section}{{\bf KalmanFull} (Basic \doxyref{Kalman}{p.}{classKalman} filter with full matrices (education purpose only)! Will be deleted soon! )}{\pageref{classKalmanFull}}{} |
---|
[32] | 41 | \item\contentsline{section}{{\bf KFcondQR} (\doxyref{Kalman}{p.}{classKalman} Filter with conditional diagonal matrices R and Q )}{\pageref{classKFcondQR}}{} |
---|
[33] | 42 | \item\contentsline{section}{{\bf KFcondR} (\doxyref{Kalman}{p.}{classKalman} Filter with conditional diagonal matrices R and Q )}{\pageref{classKFcondR}}{} |
---|
| 43 | \item\contentsline{section}{{\bf ldmat} (Matrix stored in LD form, (typically known as UD) )}{\pageref{classldmat}}{} |
---|
[91] | 44 | \item\contentsline{section}{{\bf linfn} (Class representing function $f(x) = Ax+B$ )}{\pageref{classlinfn}}{} |
---|
| 45 | \item\contentsline{section}{{\bf logger} (Class for storing results (and semi-results) of an experiment )}{\pageref{classlogger}}{} |
---|
[33] | 46 | \item\contentsline{section}{{\bf mEF} (Exponential family model )}{\pageref{classmEF}}{} |
---|
[19] | 47 | \item\contentsline{section}{{\bf MemDS} (Class representing off-line data stored in memory )}{\pageref{classMemDS}}{} |
---|
[91] | 48 | \item\contentsline{section}{{\bf memlog} (Logging into matrices in data format in memory )}{\pageref{classmemlog}}{} |
---|
[140] | 49 | \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}}{} |
---|
[32] | 50 | \item\contentsline{section}{{\bf mgamma} (Gamma random walk )}{\pageref{classmgamma}}{} |
---|
[79] | 51 | \item\contentsline{section}{{\bf mgamma\_\-fix} (Gamma random walk around a fixed point )}{\pageref{classmgamma__fix}}{} |
---|
[32] | 52 | \item\contentsline{section}{{\bf mlnorm$<$ sq\_\-T $>$} (Normal distributed linear function with linear function of mean value; )}{\pageref{classmlnorm}}{} |
---|
[140] | 53 | \item\contentsline{section}{{\bf mmix} (Mixture of mpdfs with constant weights )}{\pageref{classmmix}}{} |
---|
[4] | 54 | \item\contentsline{section}{{\bf mpdf} (Conditional probability density, e.g. modeling some dependencies )}{\pageref{classmpdf}}{} |
---|
[32] | 55 | \item\contentsline{section}{{\bf MPF$<$ BM\_\-T $>$} (Marginalized Particle filter )}{\pageref{classMPF}}{} |
---|
[145] | 56 | \item\contentsline{section}{{\bf OMpmsm} (Observation model for PMSM drive and its derivative with respect to $x$ )}{\pageref{classOMpmsm}}{} |
---|
[32] | 57 | \item\contentsline{section}{{\bf PF} (Trivial particle filter with proposal density equal to parameter evolution model )}{\pageref{classPF}}{} |
---|
[4] | 58 | \item\contentsline{section}{{\bf RV} (Class representing variables, most often random variables )}{\pageref{classRV}}{} |
---|
[8] | 59 | \item\contentsline{section}{{\bf sqmat} (Virtual class for representation of double symmetric matrices in square-root form )}{\pageref{classsqmat}}{} |
---|
[140] | 60 | \item\contentsline{section}{{\bf StringAttribute} (Class encapsulating all the necessary stuff to work with a string attribute )}{\pageref{classStringAttribute}}{} |
---|
| 61 | \item\contentsline{section}{{\bf UserInfo$<$ T $>$} (The main user info template class )}{\pageref{classUserInfo}}{} |
---|
| 62 | \item\contentsline{section}{{\bf UserInfoCore} (\doxyref{UserInfoCore}{p.}{classUserInfoCore} class is for internal purposes only. Use UserInfo$<$T$>$ instead )}{\pageref{classUserInfoCore}}{} |
---|
[3] | 63 | \end{CompactList} |
---|