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Lecturer(s)
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Course content
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1. Introduction - concepts (identification, simulation) 2. Experiment (planning, individuality, versatility, verification, experimental errors) 3. System (inputs , outputs, state, state variables, feedback) 4. Mathematically model (derivation, integration, delay) 5. Modeling of systems (abstract simulation model) 6. Basic concepts of systems theory (element, characterization, classification, continuity, confidentiality) 7. Digital computer (numerical integration, Euler's method, the accuracy of numerical solutions) 8. Modeling of random events (methods of generating random variables, characteristics) 9. Basic concepts and techniques for modeling and simulation of digital systems ( Diagnosis of logic circuits, modeling faults). 10.Example of a computer neural network model of the "back-propagation" (back-propagation)
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Learning activities and teaching methods
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Lecture
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Learning outcomes
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The course topics are focused on the methods and tools of modeling and simulation of real and designed continuous and digital systems together with practical examples.
The course focuses on understanding the modeling and simulation of physical problems. To explain the nature and interpret data, to distinguish and classify a given problem, to predict the behavior of the phenomena.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Student performance
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Recommended literature
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Burian, Z., Krejčiřík, A. (2001). Simuluj. BEN Praha.
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Cellier, F., Kofman, E. (2006). Continuous System Simulation. Springer.
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Luděk Bartoněk. (2011). MODELOVÁNÍ A SIMULACE (analogové počítače) pro obor Aplikovaná fyzika.
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Rábová,Z., Češka, M. (1982). Modelování a simulace. VUT Brno, SNTL.
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Ross, S. (2002). Simulation. Academic Press.
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Zeigler, B., Praehofer, H., Kim, T. (2000). Theory of Modeling and Simulation, second edition. Academic Press.
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