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Lecturer(s)
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Kulish Vladimír, doc. Ing. PhD., DSc.
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Namazi Hamidreza, Dr. Ph.D.
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Course content
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unspecified
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Learning activities and teaching methods
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- Class attendance
- 52 hours per semester
- Semestral paper
- 26 hours per semester
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Learning outcomes
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Complex interconnected systems, including the Internet, stock markets, human heart or brain, and many others are usually comprised of multiple subsystems that exhibit highly nonlinear deterministic as well as stochastic characteristics and are regulated hierarchically. They generate signals that exhibit complex characteristics such as nonlinearity, sensitive dependence on small disturbances, long memory, extreme variations, and non-stationarity. This introductory course is focused on integrating chaos theory and random fractal theory to analyse these complex time series (signals). Starting with the most fundamental concepts of chaos theory and random fractal theory, students gradually learn how to correctly apply the tools offered by the said theories for analysis of complex multi-fractal signals. Various example of real complex signals are considered. The curriculum of the course is structured to meet the needs of students who are analysing complex time series for their own projects, particularly those who
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Prerequisites
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Undergraduate calculus; high-school probability theory
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Assessment methods and criteria
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unspecified
Skills acquired through lectures and self-study are assessed via a written mid-term test (0?5 points) conducted midway through the semester. The score from this test is combined with the results of a written final test (0?45 points) administered at the end of the semester. A minimum of 30 points is required to qualify for pre-exam credit. Additionally, students must submit and defend their course project before the final exam. The course project is graded (0?50 points) and contributes to the total grade for the written final exam, which comprises two questions (0?25 points each). To pass the exam, students must achieve a total minimum score of 60 points.
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Recommended literature
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