Data processing techniques
Course: Applied physics, nanoelectronics and computer technology
Structural unit: Faculty of Radiophysics, Electronics and Computer Systems
Title
Data processing techniques
Code
ВК 1.6
Module type
Вибіркова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2022/2023
Semester/trimester when the component is delivered
7 Semester
Number of ECTS credits allocated
3
Learning outcomes
Fundamentals of mathematical statistics and probability theory, general approach to calculation of mechanical, electrical, optical, magnetic and other physical quantities, major experimental approaches to measurement of mechanical, electrical, optical, magnetic and other physical quantities. The role of modern scanning probe microscopy in surface nanostructures investigations. Major processing algorithms for spectra, images and N-dimensional experimental data.
Form of study
Prerequisites and co-requisites
Knowledge: major laws, equations and relations of the general physics, probability theory and other areas of higher mathematics, major modern experimental physical techniques, basics of measurement theory, basics of computer algorithms. Ability: planning and design of physical experiments, identification of practical and viable approaches to their conductance, material and technical supplies, usage of mathematical techniques, which are adequate for every particular situation.
Course content
Basics of probability theory. Measurement results as statystical values. Basics of mathematical statistics. Subjects of statistical investigations. Statistical characteristics of one-dimensional arrays of experimental data. Statistical characteristics of two-dimensional arrays of experimental data. Scanning probe microscopy images as two-dimensional data arrays and examples of their processing. Processing of data arrays with modern table processors on personal computers.
Recommended or required reading and other learning resources/tools
1. S. Cho. Numerical Calculation for Physics Laboratory Projects Using Microsoft EXCEL. – Morgan & Claypool Publishers, 2019. – 162 pp.
2. L. Lista. Statistical Methods for Data Analysis in Particle Physics - Lecture Notes in Physics 909. – Springer international Publishing Switzerland, 2016. – 205 pp.
3. D.Z. Goodson. Mathematical Methods for Physical and Analytical Chemistry. – John Wiley & Sons, Inc., 2011. – 377 pp.
Planned learning activities and teaching methods
Oral lectures using computer equipment for data processing and visualization (42 hours). Consultations in the classroom or using means of distant learning (3 hours). Self-study using the materials in the electronic form provided by the instructor and freely available software packages installed on personal computers (45 hours).
Assessment methods and criteria
Semester evaluation is performed by means of two written tests. A student can earn a maximum of 30 points for each of these tests. The final evaluation at the end of semester is performed by means of the combined written/oral test, which can give a maximum of 40 points. The course is passed with a positive grade if the total number of points obtained from all evaluations is no less than 60.
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Departments
The following departments are involved in teaching the above discipline