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Main menu for Browse IS/STAG
Course info
KMA / SC
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Course description
Department/Unit / Abbreviation
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KMA
/
SC
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Academic Year
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2024/2025
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Academic Year
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2024/2025
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Title
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Scientific computing
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Form of course completion
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Colloquium
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Form of course completion
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Colloquium
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Accredited / Credits
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Yes,
4
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Přednáška
2
[Hours/Week]
Exercise
2
[Hours/Week]
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Course credit prior to examination
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No
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Course credit prior to examination
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No
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Automatic acceptance of credit before examination
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No
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Included in study average
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NO
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Language of instruction
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Czech, English
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Occ/max
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Automatic acceptance of credit before examination
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No
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Summer semester
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0 / -
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0 / -
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0 / -
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Included in study average
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NO
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Winter semester
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0 / -
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0 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter semester
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Semester taught
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Winter semester
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Minimum (B + C) students
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not determined
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech, English
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Internship duration
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0
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No. of hours of on-premise lessons |
0
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Evaluation scale |
S|N |
Periodicity |
každý rok
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Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
Yes
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Fundamental theoretical course |
No
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Evaluation scale |
S|N |
Substituted course
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KMA/IT
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Preclusive courses
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N/A
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Prerequisite courses
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KMA/MA1 and KMA/MA2 and KMA/MA3 and KAG/LA1A and KMA/DR
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Meet all prerequisites before registering
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NO
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Informally recommended courses
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N/A
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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This course aims at several more complex problems from practice which require the use of mathematical tools from several different branches of mathematics.
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Requirements on student
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Colloquiu: active participation. presentation of a solution to a selected more complex problem
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Content
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1. Fourier methods and their application in digital music, sound processing
2. Fourier methods and their application in PDE
3. Boundary value problems -- an overview. Application to linear elasticity
4. Introduction to image processing
5. Introduction to analysis of biological signals. Application to ECG data
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Activities
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Fields of study
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Guarantors and lecturers
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Guarantors:
RNDr. Tomáš Fürst, Ph.D. ,
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Lecturer:
doc. RNDr. Eva Fišerová, Ph.D. (100%),
RNDr. Tomáš Fürst, Ph.D. (50%),
RNDr. Rostislav Vodák, Ph.D. (100%),
RNDr. Pavel Ženčák, Ph.D. (100%),
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Tutorial lecturer:
doc. RNDr. Eva Fišerová, Ph.D. (100%),
RNDr. Tomáš Fürst, Ph.D. (50%),
RNDr. Rostislav Vodák, Ph.D. (100%),
RNDr. Pavel Ženčák, Ph.D. (100%),
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Literature
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Basic:
Nathan Kutz. (2013). Data Driven Modeling & Scientific Computation. Oxford University Press.
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Basic:
Rafael C. Gonzalez, Richard E. Woods. (2017). Digital Image Processing. Pearson.
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Basic:
T. W. Körner. (1988). Fourier Analysis. Cambridge University Press; 1 edition.
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Basic:
Peter J. Brockwell, Richard A. Davis. (2009). Time Series: Theory and Methods. Springer Series in Statistics.
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Recommended:
Dave Benson. (2006). Music: A Mathematical Offering. Cambridge University Press.
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On-line library catalogues
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Prerequisites - other information about course preconditions |
Linear algebra, calculus, basic numerical mathematics, programming skills, English |
Competences acquired |
The ability to solve more complex practical problems |
Teaching methods |
- Lecture
- Dialogic Lecture (Discussion, Dialog, Brainstorming)
- Demonstration
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Assessment methods |
- Student performance
- Analysis of Creative works (Music, Pictorial,Literary)
- Seminar Work
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