/*!
\mainpage Bayesian Decision-Making toolbox for C++

\version 0.1

\author Vaclav Smidl

BDM is a collection of methods for selected tasks of Bayesian decision-making, such as estimation, filtering and control.

\section fea Features
At present the following algorithms are implemented:
- \b Bayesian \b filtering : Kalman filter, EKF, patricle filter (PF),
    - these can be combined mutualy together in mode demanding schemes, see marginalized particle filter MPF

- \b Classification using mixtures of exponential famiuly models (MixEF),
- \b Density \b estimation : using mixtures (MixEF), density composition (merger)

\section down Download and Use
The library is available under GPL, see installation instructions on page \ref install

Precompiled Mex files for use within Matlab are available \ref mexfiles

\section app Design Approach
The toolbox is designed using \b object-oriented approach with two design criteria:
\li relation to mathematics,
\li efficient evaluation,
while the first one is more important than the latter.

Hence, each mathematical object such as probability density is 
represented by one software object. The resulting algorithms are 
then implemented as operations on these objects. In cases when 
more efficient solution can be achived when this structure is not respected, 
a parallel implementation is created and clearly marked as specific. 

OpenMP is used to achive efficient implementation on parallel architectures.

\section impl Implementation

 BDM is build on top of \c IT++ which wraps numerically efficient operations of linear algebra into easy to use C++ classes. Thanks to this excellent library, writing of numerical algorithms is as easy as in Matlab but we gain significant advantages:

\li computational speed comparable to built-in Matlab function, and surpassing interpreted Matlab in order of magnitudes,
\li native support for object-oriented programming,
\li support for templates which is often more appropriate than object-oriented programming,
\li cross-platform compatibility.


*/