Learning objectives
Instruction aim
1) Knowledge and understanding
The course presents some tools for the analysis and simulation of systems for digital signal processing and communications.
2) Applying knowledge and understanding
Students learn to use tools for analysis and simulation with a “learn by doing” approach.
Prerequisites
Prerequisites
Signal Theory.
Course unit content
Outline
Laboratory of digital systems and communications. Digital filters. Audio and video signal processing. Error control. Modulation and coding.
Full programme
Lecture 1. Matlab
(Lectures 2-5) Audio signal processing
Digital filters
estimation of power spectral density
downsampling of a digital signal
signal quantization
digital signal processing of audio signals by digital filters
(Lectures 6-8) Image processing
B/W and colored images
image acquisition
image filtering
Fourier analysis of images
video signal processing (overview)
(Lectures 9-12) Digital transmission
bit error rate estimation
signal-to-noise ratio
simulations of the AWGN channel
modulation of digital signals
error control
Bibliography
Reference textbooks
A. Bruce Carlson, Paul B. Crilly: Communication systems, 5th edition, McGraw Hill, 2010.
Michael Rice: Digital Communications - A Discrete-Time Approach, Prentice Hall, 2008.
Teaching methods
Instruction methods
The course is organized in laboratory sessions and personal study for understanding the lab experiences and carrying on assigned projects. Laboratory sessions are based on the use of tools for signal processing and analysis, as well as system simulation.
Assessment methods and criteria
Evaluation methods
Evaluation comprehensively based on:
- level of (active and regular) attendance of laboratory sessions (15%)
- periodically assigned projects and reports (70%)
- oral interviews at the instructor discretion, unless exempted for a good level of course attendance (15%).
The course does not encompass exam sessions.
General information on study load and credit (CFU) acquisition:
- Overall study load for 3 CFU: about 75 hours divided in about 24 hours of in-lab activity and about 51 hours of personal work
- Every week: 2 hours in the lab and about 4 hours of personal work for understanding the lab experiences, carrying on assigned projects and writing projects reports.
Other information
The course is based on the software MATLAB