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Lecturer(s)
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Course content
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1. The age of complexity. Internet, telephone networks, power grids, transportation network, biochemical and neural networks. Why to be interested in networks? It's a small world. 2. The mathematics of networks ... is linear algebra in disguise. Measures, metrics and structures. 3. Algorithms for network analysis. 4. Network models and processes. Network formation, percolation, basic epidemiology. 5. Dynamical systems, stability, chaos and bifurcations. The language of complex systems. 6. Synchronisation. Pendulums, fire-bugs, and human hearts. 7. Self-organisation and emergent phenomena. The new mathematics of life.
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Learning activities and teaching methods
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Lecture, Demonstration
- Attendace
- 26 hours per semester
- Preparation for the Exam
- 34 hours per semester
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Learning outcomes
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To understand the mathematics of complex networks. To understand models of network processes.
Comprehension Comprehension of complex networks, ability to solve practical problems.
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Prerequisites
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Some linear algebra, basic ordinary and partial differential equations, programming (MatLab, SciLab or Octave are preferred), English (all course materials are in English).
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Assessment methods and criteria
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Oral exam, Seminar Work
Exam: a working sotware code and demostrated comprehension of basic principles.
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Recommended literature
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Online přednáška.
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Newman, M. (2010). Networks. An Introduction. Oxford.
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Reuven Cohen, Shlomo Havlin. (2010). Complex Networks: Structure, Robustness and Function. Cambridge University Press.
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V. Latora, V. Nicosia, G. Russo, Complex Networks. (2017). Principles, Methods and Applications. Cambridge University Press.
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