Lecturer(s)
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Course content
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Advanced matrix calculus. Numerical mathematics. Graphs and nets. Tensor calculus. Partial differential equation and their systems. Extensive systems of linear differential equations. Selected systems of the non-linear differential equations. Integral equations. Variation calculus with applications. Stability of solution in mathematics.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming)
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Learning outcomes
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The target of the subject is to deepen and extend the mathematical knowledge in the selected mathematical areas and to provide them the tools that are necessary for the solution of the problems
Student will be able to use these methods independently at the solution of the concrete examples from the branch of student´s doctoral study
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Prerequisites
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Knowledge of mathematics and probability is assumed in the range that is usual at the technical universities
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Assessment methods and criteria
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Oral examination
Student must be able to make the prescribed subject matted up from the theoretical and practical view.
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Recommended literature
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BARTÁK, L.; HERRMANN, L.; LOVICAR, V.; VEJVODA, O. Parciální diferenciální rovnice. SNTL, Praha, 1998.
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BENSOUSSAN, A.; LIONS, J. L. Impulsnoje upravlenje i kvazivariacionnyje neravenstva. Nauka, Moskva, 1987.
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Leon, S.J. Linear Algebra with Applications. New Jersey, Prentice Hall, 1994.
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V. M.; FOMIN, S. V.; TICHOMIROV, V. M. Matematická teorie optimálních procesů. Academia, Praha, 1991.
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