Servizi per la didattica
PORTALE DELLA DIDATTICA

Compressed sensing: theory and applications

01QRQRV

A.A. 2018/19

Course Language

Inglese

Course degree

Doctorate Research in Ingegneria Elettrica, Elettronica E Delle Comunicazioni - Torino

Course structure
Teaching Hours
Lezioni 20
Teachers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Magli Enrico Professore Ordinario ING-INF/03 20 0 0 0 3
Teaching assistant
Espandi

Context
SSD CFU Activities Area context
*** N/A ***    
2018/19
PERIOD: FEBRUARY This course will provide students with theoretical and practical knowledge of a new and stimulating research area, namely compressed sensing. This topic was initially driven by imaging applications, but is appealing for many areas of engineering and mathematics, due to the extremely large number and type of possible applications.
PERIOD: FEBRUARY This course will provide students with theoretical and practical knowledge of a new and stimulating research area, namely compressed sensing. This topic was initially driven by imaging applications, but is appealing for many areas of engineering and mathematics, due to the extremely large number and type of possible applications.
This course covers the topic of compressed sensing, an innovative signal sensing and representation paradigm that is significantly more efficient than conventional sampling as described by Shannon’s theorem. Compressed sensing represents a signal through a small set of linear projections of the signal samples; the original samples can be reconstructed via a nonlinear process. This very compact representation has many potential advantages in the areas of signal acquisition and communication, as well as visual information processing. The course will address the theory of compressed sensing and its practical applications. It will involve 15 hours, divided into 12 hours of lectures and 3 hours of computer labs using Matlab, where the students will become familiar with compressed sensing algorithms using a hands-on approach. The lectures will cover both theory and applications. The course will start with the introduction of the mathematical aspects of compressed sensing, including deterministic reconstruction conditions, the restricted isometry property, and reconstruction algorithms such as basis pursuit, orthogonal matching pursuit, and iterative thresholding. After that, the course will address a few key applications of compressed sensing, with particular regard to communications, applications to visual signals, and implementation aspects.
This course covers the topic of compressed sensing, an innovative signal sensing and representation paradigm that is significantly more efficient than conventional sampling as described by Shannon’s theorem. Compressed sensing represents a signal through a small set of linear projections of the signal samples; the original samples can be reconstructed via a nonlinear process. This very compact representation has many potential advantages in the areas of signal acquisition and communication, as well as visual information processing. The course will address the theory of compressed sensing and its practical applications. It will involve 15 hours, divided into 12 hours of lectures and 3 hours of computer labs using Matlab, where the students will become familiar with compressed sensing algorithms using a hands-on approach. The lectures will cover both theory and applications. The course will start with the introduction of the mathematical aspects of compressed sensing, including deterministic reconstruction conditions, the restricted isometry property, and reconstruction algorithms such as basis pursuit, orthogonal matching pursuit, and iterative thresholding. After that, the course will address a few key applications of compressed sensing, with particular regard to communications, applications to visual signals, and implementation aspects.
Modalità di esame:
Exam:
Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
Exam:
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.
Esporta Word


© Politecnico di Torino
Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY
Contatti