Nonlinear and Information Analysis in Biomedicine
Code  Completion  Credits  Range  Language 

17DANEIA  ZK  5  2P  English 
 Lecturer:
 Tutor:
 Supervisor:
 Department of Information and Communication Technology in Medicine
 Synopsis:

Summary of practical applications of fractal an multifractal analysis, applied to biological timeseries. 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. Highdimensional chaos. Multifractal formalism, estimators of Hurst exponents, selfsimilarity 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 dataanalysis project.
 Syllabus of lectures:

Summary of practical applications of fractal an multifractal analysis, applied to biological timeseries. 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. Highdimensional chaos. Multifractal formalism, estimators of Hurst exponents, selfsimilarity 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 0486439186
Stanford Goldman. Information Theory. New York: Prentice Hall, 4th edition 2005 ISBN
0486442713
Raymond W. Yeung. Information Theory and Network Coding Springer 2008, 2002. ISBN 9780387792330 Thomas
M. Cover, Joy A. Thomas. Elements of information theory, 2nd Edition. New York: WileyInterscience, 2006. ISBN 0471241954
 Note:
 Further information:
 No timetable has been prepared for this course
 The course is a part of the following study plans: