SubjectsSubjects(version: 849)
Course, academic year 2019/2020
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Measurement and data processing in material science - NEVF112
Title in English: Měření a zpracování dat v materiálovém výzkumu
Guaranteed by: Department of Surface and Plasma Science (32-KFPP)
Faculty: Faculty of Mathematics and Physics
Actual: from 2018
Semester: winter
E-Credits: 3
Hours per week, examination: winter s.:2/0 Ex [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Guarantor: doc. RNDr. Karel Mašek, Dr.
RNDr. Viktor Johánek, Ph.D.
Annotation -
Last update: doc. RNDr. Jiří Pavlů, Ph.D. (24.01.2018)
Computer acquisition and control in experiment, sensors, transducers. Analog measurement systems, signal processing, noise. Digitalization, A/D and D/A converters. Time series, logic signals, counters. Measurement of analogue and digital signals in electron spectroscopy. Image acquirement and analysis. Data collection and processing software.
Course completion requirements - Czech
Last update: doc. RNDr. Jiří Pavlů, Ph.D. (14.06.2019)

Podmínkou zakončení předmětu je úspěšné složení zkoušky, tj. hodnocení zkoušky známkou "výborně", "velmi dobře" nebo "dobře". Zkouška musí být složena v období předepsaném harmonogramem akademického roku, ve kterém student předmět zapsal.

Literature - Czech
Last update: doc. RNDr. Jiří Pavlů, Ph.D. (24.01.2018)

Meloun M., Militký J.: Statistické zpracování experimentálních dat, edice Plus, Praha 1994.

Anděl J.: Matematická statistika, SNTL, Praha 1978.

Press W.H. et al.: Numerical Recipes , Cambridge University Press, Cambridge, 1992.

Tutubalin V.N.: Teorie pravděpodobnosti, SNTL, Praha 1978.

Requirements to the exam -
Last update: doc. RNDr. Karel Mašek, Dr. (09.10.2017)

Examination is oral. Scope of the examination corresponds to the sylabus to the extent presented at the lectures.

Syllabus -
Last update: doc. RNDr. Jiří Pavlů, Ph.D. (24.01.2018)
Basics:
Experiment in physics and its automation, computer controlled experiment, physical quantities and their conversions, sensors and transducers (passive, active, w/feedback)

Analog signals:
Standards and calibration, role of reference and background, conditioning of analog (and digital) signals, synchronous detection, types of signal sources and measurement systems, spectral analysis, sources and types of noise in measurements, noise coupling, balanced systems

Digital signals:
Conversion of analog signal to digital (digitization) and backwards, signal sampling, Nyquist theorem and aliasing, quantization and coding, sources and types of conversion errors, dithering, examples of A/D and D/A converters, multichannel conversion

Time series:
Logic signals, timing of logic signals and timing errors, time and frequency measurement (clocks, counters, indirect and direct methods), on-line and off-line data processing, spectral response of linear systems, convolution, interpolation, filtration, time series relationships, other manipulations in time domain (resampling, joining, synchronization)

Measurement of analogue and digital signals in electron spectroscopy:
Basics of electron spectroscopy, measurement methods, spectra processing (fitting, background subtraction, filtering, …), data file formats, spectroscopic data collection and processing software (SpecsLab, WSpectra, FITT, …), data collection and processing using LabView, visualisation, analysis and presentation of experimental data using Igor Pro and Origin Pro

Methods of image measurement and analysis:
Image acquirement, processing and analysis, types of images, corrections of imaging system distortions, calibration and spectral analysis of images, filtration, thresholding, measurement of distances and sizes of objects, examples of diffraction pattern processing, description of island structures, processing of scanning microscopy images

 
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