DE0493 Digital Signal Processing

Code DE0493
Name Digital Signal Processing
Status Compulsory/Courses of Limited Choice
Level and type Undergraduate Studies, Academic
Field of study Electronics and Telecommunications
Faculty Faculty of Computer Science, Information Technology and Energy
Academic staff Anna Litviņenko, Deniss Kolosovs
Credit points 3.0
Parts 1
Annotation Within the framework of the course the following topics are covered: sampling theorem; signal conversion from an analogue to a digital form without aliasing; interrelation between frequency response, impulse response and difference equation; implementation of finite and infinite impulse response filters by means of signal processors; orthogonal and non-orthogonal digital transformations; impact of quantization errors on signal representation quality..
Contents
Content Full- and part-time intramural studies Part time extramural studies
Contact hours Independent work Contact hours Independent work
Linear time-invariant two-port characteristics 4 6 1 6
Analogue filter design 4 6 1 6
Continuous signal conversion into a digital form 2 3 1 3
Design and implementation of finite and infinite impulse response filters 6 9 1 9
Fourier transform and other digital transformations 6 9 1 9
Sampling frequency conversion 2 3 1 3
Impact of quantization and sampling errors 4 6 1 6
Non-uniform sampling characteristics 4 6 1 6
Total: 32 48 8 48
Goals and objectives
of the course in terms
of competences and skills 		The goal of the course: to acquire basic knowledge about the sampling theorem and signal conversion from an analogue to a digital form without aliasing. The objectives are the following: to develop skills that are essential to choose sampling and quantization parameters of continuous signals; to enable students to use interrelation between frequency response, impulse response and difference equation in order to design finite and infinite impulse response filters; to improve the students' ability to evaluate the impact of digital transformations and quantization errors on signal representation quality.
Learning outcomes
and assessment 		Implementation of finite and infinite impulse response filters based on frequency response. Simulation of digital filters in MatLab environment. - Tests, Reports, Exam
Implementation of finite and infinite impulse response filters based on impulse response. Simulation of digital filters in MatLab environment. - Tests, Reports, Exam
Implementation of finite and infinite impulse response filters based on difference equation. Simulation of digital filters in MatLab environment. - Tests, Reports, Exam
Implementation of finite and infinite impulse response filters based on canonical, cascade and parallel structures. Simulation of digital filters in LabView environment. - Tests, Reports, Exam
Evaluation criteria of study results
Tests - 20%
Reports and their defence - 30%
Exam - 50%
 
Course prerequisites Basic computer skills; theory of complex variable; relations between contiguous and digital signals and their spectra; application of logical and numerical functions; fixed- and floating-point arithmetic.
Course planning
Part CP Hours Tests
Lectures Practical Lab. Test Exam Work
1 3.0 20.0 20.0 0.0 *
[Extended course information PDF]