Bi0440 Actual Trends Data Analysis

Faculty of Science
Spring 2009
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Daniel Schwarz, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: doc. Ing. Daniel Schwarz, Ph.D.
Timetable
Tue 15:00–16:50 F01B1/709
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
There is a considerable increase in the amount of data, which represent processes, events and activities in living systems, together with the rapid developments in digital technology which allow us to acquire, transmit and store the data. Thus, there is also an increase in the importance of methods for digital signal processing and analysis. The goal of signal processing is to enhance signal components in noisy measurements or to transform measured data sets such that new features become visible. This course is focused on current advancements in this field. Main objectives can be summarized as follows: extending students’ knowledge about methods for signal processing and analysis; understanding of the potential applications of these methods for a computational biologist; assumption of methods for denoising in measured data; introducing the field of time-frequency and wavelet analysis.
Syllabus
  • Signals and systems – introduction or revision: classification and examples of signals, classification and examples of systems;
  • Discrete-time signals and their frequency analysis;
  • Time-frequency description of signals, short-time Fourier transform;
  • Wavlet decomposition of signals, spectrogram;
  • Wavelet transform;
  • Data processing and analysis with the use of wavelet transform;
  • Other applications of wavelet transformation;
Literature
  • DEVASAHAYAM, Suresh R. Signals and systems in biomedical engineering : signal processing and physiological systems modeling. 1st ed. New York: Kluwer Academic/Plenum Publishers, 2000, xvi, 337. ISBN 0306463911. info
  • DRONGELEN, Wim van. Signal processing for neuroscientists : introduction to the analysis of physiological signals. Amsterdam: Academic Press, 2007, ix, 308. ISBN 9780123708670. info
  • Wavelets and their applications. Edited by Michel Misiti. London: ISTE, 2006, 330 s. ISBN 9781905209316. info
Assessment methods
Teaching methods: lectures, demonstration of selected algorithms on a computer.
Final requirements: oral exam
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is also listed under the following terms Spring 2008 - for the purpose of the accreditation, Autumn 2010 - only for the accreditation, Spring 2006, Spring 2007, Spring 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2011 - acreditation, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, autumn 2021.
  • Enrolment Statistics (Spring 2009, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2009/Bi0440