| 1 | /*! |
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| 2 | \mainpage Bayesian Decision-Making toolbox for C++ |
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| 3 | |
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| 4 | \version 0.1 |
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| 5 | |
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| 6 | \author Vaclav Smidl |
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| 7 | |
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| 8 | BDM is a collection of methods for selected tasks of Bayesian decision-making, such as estimation, filtering and control. |
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| 9 | It is implemneted in C++ with available interfaces to matlab (called bdmtoolbox) and Python (preliminary). |
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| 10 | |
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| 11 | \section fea Features |
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| 12 | At present the following algorithms are implemented: |
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| 13 | - \b Bayesian \b filtering : Kalman filter, EKF, patricle filter (PF), |
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| 14 | - these can be combined mutualy together in mode demanding schemes, see marginalized particle filter MPF |
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| 15 | |
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| 16 | - \b Classification using mixtures of exponential famiuly models (MixEF), |
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| 17 | - \b Density \b estimation : using mixtures (MixEF), density composition (merger) |
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| 18 | - \b LQG \b control : so far only for ARX and Kalman filters |
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| 19 | |
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| 20 | \section down Download and Use |
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| 21 | The library is available under GPL, see installation instructions on page \ref install |
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| 22 | |
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| 23 | It is split into library and applications. One of the applications is toolbox for matlab, which can be downloaded in binary form for win32, see \ref install. |
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| 24 | |
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| 25 | \section app Publications |
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| 26 | |
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| 27 | Publications that were made with the toolbox are: |
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| 28 | - \b Software papers: Fusion 2010 |
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| 29 | - \b Distributed \b identification : <a href="http://library.utia.cas.cz/separaty/2009/AS/smidl-log-normal%20merging%20for%20distributed%20system%20identification.pdf"> SYSID 09 </a> |
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| 30 | - \b Baysian \b filtering : <a href="http://library.utia.cas.cz/separaty/2009/AS/smidl-challenges%20and%20limits%20of%20extended%20kalman%20filter%20based%20sensorless%20control%20of%20permanent%20magnet%20synchronous%20machine%20drives.pdf"> EPE 09 </a> |
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| 31 | |
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| 32 | The status of replicability of the published experiments is available in \ref published. |
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| 33 | |
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| 34 | \section impl Implementation |
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| 35 | |
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| 36 | BDM is build on top of \c IT++ which wraps numerically efficient operations of linear algebra into easy to use C++ classes with Matlab-like syntax. |
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| 37 | */ |
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