717-2961/01 – Computer Processing of Experimental Data (PZED)

Gurantor department	Department of Physics	Credits	3
Subject guarantor	doc. RNDr. Dalibor Ciprian, Ph.D.	Subject version guarantor	doc. RNDr. Dalibor Ciprian, Ph.D.
Study level	undergraduate or graduate	Requirement	Compulsory
Year	2	Semester	winter
		Study language	Czech
Year of introduction	2016/2017	Year of cancellation	2017/2018
Intended for the faculties	FMT, USP, FEI	Intended for study types	Bachelor

Instruction secured by
Login	Name	Tuitor	Teacher giving lectures
CIP10	doc. RNDr. Dalibor Ciprian, Ph.D.

Extent of instruction for forms of study
Form of study	Way of compl.	Extent
Full-time	Graded credit	1+2

Subject aims expressed by acquired skills and competences

The objective of the course is to teach the students how to apply the data processing and evaluation methods to the results obtained from various experimental techniques used in physics and chemistry.

Teaching methods

Lectures
Seminars
Tutorials

Summary

The course extends the knowledge in the field of data evaluation using computers. The emphasis is placed on practical lectures in computer laboratory. The data evaluation methods are presented in MATLAB programming language, and demonstrated using the results obtained either from computer models or from real expriments.

Compulsory literature:

Mathworks Inc.: MATLAB R13 HELP, Mathworks Inc., 2002. BEVINGTON, P., KEITH ROBINSON, D. Data Reduction and Error Analysis for the Physical Sciences 3rd Edition, McGraw-Hill, 2015, ISBN 978-0072472271

Recommended literature:

CHAPRA, S. C. Applied Numerical Methods with MATLAB for Engineers and Scientists, McGraw-Hill, 2012, ISBN 978-0-07-340110-2

Way of continuous check of knowledge in the course of semester

discussion with students during the lessons

E-learning

no e-lerining available

Other requirements

There are not any additional requests.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Introduction to MATLAB programming language, import of data 2. Script writting and debugging 3. MATLAB toolboxes and their applications 4. User functions writting 5. The ideal, natural and immediate sampling, Shannon - Kotelnik theorem. 6. Statistical analysis of univariate data. 7. Numeric smmothing and experimental data filtering. 8. Data convolution and deconvolution. 9. Nonparametric data regression, signal differentiation and integration. 10. Parametric regression - linear and nonlinear models. 11. Fourier analysis and its applications 12. Wavelet analysis and its applications

Conditions for subject completion

Full-time form (validity from: 2016/2017 Winter semester, validity until: 2017/2018 Summer semester)

Task name	Type of task	Max. number of points (act. for subtasks)	Min. number of points	Max. počet pokusů
Graded credit	Graded credit	100	51	3

Mandatory attendence participation:

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Conditions for subject completion and attendance at the exercises within ISP:

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Occurrence in study plans

Academic year	Programme	Branch/spec.	Spec.	Zaměření	Form	Study language	Tut. centre	Year	W	S	Type of duty
2017/2018	(B3942) Nanotechnology	(3942R001) Nanotechnology			P	Czech	Ostrava	2			Compulsory	study plan
2016/2017	(B3942) Nanotechnology	(3942R001) Nanotechnology			P	Czech	Ostrava	2			Compulsory	study plan

Occurrence in special blocks

Block name	Academic year	Form of study	Study language	Year	W	S	Type of block	Block owner

Assessment of instruction

2017/2018 Winter

2016/2017 Winter