Enrollment year
2017/2018
Academic discipline
ING-INF/03 (TELECOMMUNICATIONS)
Department
DEPARTMENT OF ELECTRICAL,COMPUTER AND BIOMEDICAL ENGINEERING
Course
ELECTRONIC ENGINEERING
Curriculum
Space Communication and Sensing
Period
1st semester (01/10/2018 - 18/01/2019)
Lesson hours
50 lesson hours
Activity type
WRITTEN AND ORAL TEST
Prerequisites
Basic concepts in continuous time signal theory.
Learning outcomes
Mathematical treatment of time-discrete signals and systems:
. Z-transform of signals represented by difference equations;
. design of digital filters for deterministic and stochastic signals;
. spectrum estimation for discrete-time signals;
. optimal filtering and adaptive filter design.
Course contents
Introduction to digital signal theory.
Discrete time signals, sampling theorem, linear shift invariant digital systems.
Analysis of digital systems in the Fourier and Z transform domains.
Discrete-time random processes.
Digital filtering of deterministic and stochastic signals.
Deterministic and stochastic signal modeling.
Wiener Filter: linear prediction, white noise filtering, unwanted signal canceling.
Adaptive filtering: LMS, RLS and Kalman algorithms.
Application examples in Matlab and programmable hardware platforms.
Teaching methods
Lectures (hours/year in lecture theatre): 44
Practical class (hours/year in lecture theatre): 0
Practicals / Workshops (hours/year in lecture theatre): 8
Reccomended or required readings
Monson H. Hayes Statistical Digital Signal Processing and Modeling. John Wiley & Sons Inc, 1996.
Assessment methods
The exam consists of an oral test during which questions will be asked on two/three different topics regarding the basic mathematical techniques, signal characterization, and filtering, in order to cover most of the course topics.
Alternatively, each student can choose to implement a laboratory project, assigned by the teacher, followed by an in-depth interview. The assigned projects will cover most of the course topics.
The final mark is in thirtieths.
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