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Lecturer(s)
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Kulička Jiří, Mgr. Ph.D.
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Jehlička Vladimír, doc. Ing. CSc.
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Course content
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Errors and their classification. Conditionality of tasks and stability of algorithms. Approximation of functions and its properties. Numerical solution of equations and their systems. Numerical integration and derivation. Numerical solution of differential equations and their systems. Optimalization. Programming numerical algorithms in Matlab.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Work with text (with textbook, with book), Demonstration
- Contact teaching
- 20 hours per semester
- Preparation for an exam
- 80 hours per semester
- Home preparation for classes
- 80 hours per semester
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Learning outcomes
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The aim of the course is to introduce students to the basic algorithms of numerical mathematics such as: errors and their classification, conditionality of problems and stability of algorithms, approximation of functions and its properties, numerical solution of equations and their systems, numerical integration and derivatives, numerical solution of differential equations and solution of optimization problems. The course also includes programming of numerical algorithms in Matlab.
The graduate can assess basic numerical methods and design their application.
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Prerequisites
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Knowledge of studying mathematics at the undergraduate level is assumed.
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Assessment methods and criteria
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Oral examination, Written examination
Preparation of one seminar paper according to the assignment, which will be specified during the semester. The exam has two parts: theoretical and practical. In the theoretical part, the student answers a set of questions from the area of basic terms, definitions and sentences. In the practical part, he will solve a set of problems, where he will demonstrate his ability to apply the mentioned algorithms to a specific problem.
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Recommended literature
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Kulička, Jiří. Elementární algoritmy aplikované matematiky . Pardubice: Univerzita Pardubice, 2016. ISBN 978-80-7395-972-2.
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