Advanced Digital Signal Processing

Course: Computer Systems and Networks

Structural unit: Faculty of Radiophysics, Electronics and Computer Systems

Title
Advanced Digital Signal Processing
Code
ОК 12
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2022/2023
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
5
Learning outcomes
The student must know: Mathematical foundations, base principles and methods of modern digital signal processing, which they will be able to use in solving engineering problems, primarily in the analysis of experimental data and in the development of radio signal and multimedia information processing systems. The student must be able to: Use the wavelet transform to solve practical problems, solve incorrect problems using standard libraries, design adaptive filters to suppress noise interference, and develop appropriate software.
Form of study
Full-time form
Prerequisites and co-requisites
Before studying the discipline "Advanced digital signal processing", students need to master the basics of mathematical analysis and linear algebra, taught in the undergraduate discipline "Higher mathematics", the basic concepts of physics and electrical engineering, taught in the disciplines "General physics" and "Theory of electric and magnetic circles" and the fundamental concepts of digital signal processing, which are presented in the discipline "Digital signal processing".
Course content
The discipline "Advanced digital signal processing" includes basic information on the theory and methods of solving ill-posed problems, construction of adaptive filters, and applications of the wavelet transform for data processing. In addition, students get acquainted with the main approaches to the hardware implementation of digital filters and with the problems that arise. The main concepts studied within the framework of this discipline are illustrated by examples of their application in real experimental data processing systems.
Recommended or required reading and other learning resources/tools
1. О.В.Барабанов. Основи цифрової обробки сигналів. Навчальний посібник, видавнича лабораторія ФРЕКС КНУ імені Т.Шевченка. – 2013. - 120 с. 2. Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to Digital Signal Processing. - 1045p. 3. Richard G. Lyons. Understanding Digital Signal Processing. - 612 p. 4. A.V.Oppenheim and R.W.Schafer. Discrete-Time Signal Processing // Prentice-Hall, 3Ed. - 890 p. 5. William D. Stanley. Digital Signal Processing. 6. J.G.Proakis and D.G.Manolakis. Digital Signal Processing: Principles, Algorithms and Applications. - 945 p. 7. Rabiner, Lawrence R. Multirate Digital Signal Processing // Prentice-Hall Series in Signal Processing. - 1983.
Planned learning activities and teaching methods
Lectures, laboratory classes, unsupervised work.
Assessment methods and criteria
- Semester assessment. After each of two semantic modules the written test is carried out, the result of each test is scored from 0 to 30 points. -Final assessment. The written examination is carried out at the end of semester; the permit to examination is given if the subtotal result of two tests is no less then 30 points; examination test consists of 2 tasks and two problems, the performance of each task and solution of each problem is scored from 0 to 10 points. The result of learning of the subject is considered positive if the total score for semantic modules and exam exceeds 60 points, the score for exam must be higher than 20 points.
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Departments

The following departments are involved in teaching the above discipline