Terminated in academic year 2021/2022

Applied Artificial Intelligence Methods

Type of study	Follow-up Master
Language of instruction	English
Code	450-4049/02
Abbreviation	AUI
Course title	Applied Artificial Intelligence Methods
Credits	4
Coordinating department	Department of Cybernetics and Biomedical Engineering
Course coordinator	prof. Ing. Martin Černý, Ph.D.

Subject syllabus

Lectures:
1. Introduction on artificial intelligence scientific field
2. Principles of artificial intelligence, importace of knowledge in problem solving tasks
3. Methods of computer knowledge reprezentation
4. Mathematic and linguistc modelling
5. Vagueness formalization of knowledge in linguistic models
6. Principles of fuzzy set and fuzy logic theory
7. Fuzzy models of Mandami type
8. Fuzzy models of Takagi-Sugeno type
9. Diagnostoc expert systems
10. Fuzzy controllers
11. Topology and functions of multilayer artificial neural networks
12. Neural networks application in biomedical engineering
13. Genetic algorithms - versatil optimization methods
14. Genetic algorithms application in adaptation procedures

Laboratories:
1. Fuzzy controller using microcomputer and PLC

Computer labs:
1. Computer system MATLAB
2. Fuzzy ToolBox in MATLAB
3. Fuzzy sets and vagueness objects reprezentation in MATLAB
4. Fuzzy conditonal rules formalization in MATLAB
5. Fuzzy modelling of Mandami type in MATLAB
6. Fuzzy modelling of Takagi-Sugeno type in MATLAB
7. Diagnostic fuzzy expert systems
8. Fuzzy controllers in MATLAB
9. Pletysmogram evaluation fuzzy expert module
10. EEG evaluation fuzzy expert module
11. Neural network synthesi in Neural ToolBoxu of MATLABu
12. Neural network application in biomedical engineering
13. Genetic algorithm synthesis in MATLAB

Literature

RUSSEL,S., NORVIG,P.: Artificial Intelligence, Prentice-Hall, Inc., 2003,
LUGER,G.F., STUBBLEFIELD,W.A.: Artificial Intelligence, The Benjamin/Cummings Publishing Company, Inc., 2009,
ZIMMERMANN,H.J. Fuzzy Set Theory - and Its Applications. Kluwer Academic Publishers, 2001.
HUDSON, D. L. a M. E. COHEN. Neural networks and artificial intelligence for biomedical engineering. New York: Institute of Electrical and Electronics Engineers, c2000. .
AGAH, Arvin. Medical applications of artificial intelligence. Boca Raton: CRC Press/Taylor & Francis Group, 2014. .
SILER, William a BUCKLEY, James J. Fuzzy expert systems and fuzzy reasoning. Hoboken: John Wiley, 2005. .
AKAY, Metin (ed.). Nonlinear biomedical signal processing. Volume I, Fuzzy logic, neural networks, and new algorithms. IEEE Press series on biomedical engineering. New York: IEEE Press, c2000. ISBN 0-7803-6011-7.

Advised literature

C. R. REEVES, J. E. ROW,. Genetic Algorithms: Principles and Perspectives. Kluwer Academic Publishers, New York, 2002.
GRAUPE,D. Principles of Artificial Neural Netvorks. World Scientific. 2013.
BEGG, Rezaul., Daniel T. H. LAI a Marimuthu. PALANISWAMI. Computational intelligence in biomedical engineering. Boca Raton: CRC Press, c2008. .
SHUKLA, Anupam a Ritu TIWARI. Intelligent medical technologies and biomedical engineering: tools and applications. Hershey, PA: Medical Information Science Reference, c2010. .

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