Revision 1044, 1.1 kB
(checked in by smidl, 15 years ago)
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Tutorial moved to bdmtoolbox
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1 | /*! |
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2 | \page bdt_scenarios Basic Scenarios of BDMToolbox |
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3 | |
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4 | The basic elements of BDM are: |
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5 | -# probability density functions, (bdm::pdf), both conditional and unconditional |
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6 | -# functions, (bdm::fnc), of vector arguments |
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7 | -# Bayesian estimators (bdm::BM), providing variaous exact and approximate algorithms for Bayesian inference |
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8 | -# Data Sources (bdm::DS), providing access to various form of recursive data |
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9 | -# Controllers (bdm::Controller), generating control strategies, both feedback, or feedforward |
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10 | -# Loggers (bdm::logger), for storing results of experiments |
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12 | The objects are designed to allow mutual combination of these. Distinction of what needs to be connected where is provided by class RV which stands for random variable. |
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13 | |
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14 | Predefined scenarios implemented in mex are: |
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15 | |
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16 | - Simulation, see \ref simulator.cpp |
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17 | - Estimation, see \ref estimator.cpp |
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18 | - Controll Loop, see \ref controlloop.cpp |
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19 | - Multiple-Participant Decision-Making, see \ref arena.cpp |
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21 | For details of their use, see tutorials: |
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22 | - \ref userguide_pdf |
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23 | - \ref userguide_sim |
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24 | - \ref userguide_estim |
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25 | - \ref userguide_ctrl |
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28 | |
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29 | */ |
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