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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2023/2024
UPOZORNĚNÍ: Jsou dostupné studijní plány pro následující akademický rok.

Nonlinear and Information Analysis in Biomedicine

The course is not on the list Without time-table
Code Completion Credits Range Language
17DBNEIA ZK 5 2P Czech
Garant předmětu:
Lecturer:
Tutor:
Supervisor:
Department of Information and Communication Technology in Medicine
Synopsis:

Summary of practical applications of fractal an multifractal analysis, applied to biological time-series. Introduction to deterministic chaos. Takens theorem, practical computation of selected invariant parameters from experimental data (correlation dimension, Lyapunov exponents etc.). Tests for determinism and nonlinearity. High-dimensional chaos. Multifractal formalism, estimators of Hurst exponents, self-similarity of time series. Information entropy, applications. Average mutual information. Continuous and discrete communication channel. Relationship of information and thermodynamic entropy. Principle of maximal entropy. Biosystem organization, models and system identification. Introduction of statistical decision making, testing of statistical hypothesis, Bayessian approach.

Requirements:

Solved and documented individual software/biomedical nonlinear data-analysis project.

Syllabus of lectures:

Summary of practical applications of fractal an multifractal analysis, applied to biological time-series. Introduction to deterministic chaos. Takens theorem, practical computation of selected invariant parameters from experimental data (correlation dimension, Lyapunov exponents etc.). Tests for determinism and nonlinearity. High-dimensional chaos. Multifractal formalism, estimators of Hurst exponents, self-similarity of time series. Information entropy, applications. Average mutual information. Continuous and discrete communication channel. Relationship of information and thermodynamic entropy. Principle of maximal entropy. Biosystem organization, models and system identification. Introduction of statistical decision making, testing of statistical hypothesis, Bayessian approach.

Syllabus of tutorials:
Study Objective:
Study materials:

Leon Brillouin, Science and Information Theory, Mineola, N.Y.: Dover, 3rd edition 2004. ISBN 0-486-43918-6

Stanford Goldman. Information Theory. New York: Prentice Hall, 4th edition 2005 ISBN

0-486-44271-3

Raymond W. Yeung. Information Theory and Network Coding Springer 2008, 2002. ISBN 978-0-387-79233-0 Thomas

M. Cover, Joy A. Thomas. Elements of information theory, 2nd Edition. New York: Wiley-Interscience, 2006. ISBN 0-471-24195-4

Note:
Further information:
Course may be repeated
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-03-27
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