Gurantor department | Department of Applied Mathematics | Credits | 4 |

Subject guarantor | Ing. Jan Kracík, Ph.D. | Subject version guarantor | Ing. Jan Kracík, Ph.D. |

Study level | undergraduate or graduate | Requirement | Compulsory |

Year | 3 | Semester | summer |

Study language | Czech | ||

Year of introduction | 2019/2020 | Year of cancellation | |

Intended for the faculties | FEI | Intended for study types | Bachelor |

Instruction secured by | |||
---|---|---|---|

Login | Name | Tuitor | Teacher giving lectures |

KRA0220 | Ing. Jan Kracík, Ph.D. |

Extent of instruction for forms of study | ||
---|---|---|

Form of study | Way of compl. | Extent |

Full-time | Graded credit | 0+2 |

Part-time | Graded credit | 0+8 |

Students get acquainted with a probabilistic approach to uncertainty in real world models.

Tutorials

Project work

Mathematical models of real world systems are often loaded with uncertainty caused by random input parameters, model imprecision, imprecise data, etc. Probability theory is often used for repreenting quantifying the uncertainty in the models.

JAYNES, Edwin T., BRETTHORST, G. Larry, ed. Probability theory: the logic of science. Cambridge: Cambridge University Press, 2003. ISBN 0-521-59271-2.
ROBERT, Christian P. a George. CASELLA. Monte Carlo statistical methods. 2nd ed. New York: Springer, c2004. ISBN 0-387-21239-6.

W.H. Press, B.P. Flannery, S.A. Teukolski, W.T. Vetterling, Numerical Recipes in C. Cambridge University Press, 1990.
W. E. Boyce, R. C. DiPrima: Elementary differential equations. Wiley, New York 1992

semestral project

There are not defined other requirements for student.

Subject has no prerequisities.

Subject has no co-requisities.

Static models with random inputs
Monte Carlo methods
Linear dynamical models with Gaussian noise
Kalman filter
Bayesian approach to inverse problems

Task name | Type of task | Max. number of points
(act. for subtasks) | Min. number of points |
---|---|---|---|

Graded credit | Graded credit | 100 | 51 |

Show history

Academic year | Programme | Field of study | Spec. | Zaměření | Form | Study language | Tut. centre | Year | W | S | Type of duty | |
---|---|---|---|---|---|---|---|---|---|---|---|---|

2020/2021 | (B0541A170008) Computational and Applied Mathematics | P | Czech | Ostrava | 3 | Compulsory | study plan | |||||

2020/2021 | (B0541A170008) Computational and Applied Mathematics | K | Czech | Ostrava | 3 | Compulsory | study plan | |||||

2019/2020 | (B0541A170008) Computational and Applied Mathematics | P | Czech | Ostrava | 3 | Compulsory | study plan | |||||

2019/2020 | (B0541A170008) Computational and Applied Mathematics | K | Czech | Ostrava | 3 | Compulsory | study plan |

Block name | Academic year | Form of study | Study language | Year | W | S | Type of block | Block owner |
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