Escuela Técnica Superior de
Ingeniería y Sistemas de Telecomunicación
Universidad Politécnica de Madrid

Seminarios de investigación curso 2019/2020

(*) Important note on certificates of achievement: these certificates will only be issued to persons who attend all the sessions of the seminar and pass the evaluation activities that the teachers will propose.

Semestre de OTOÑO / FALL semester

  • Optical communications (17-18 Oct. 2019)
  • Image and Video Coding (25-26 Sept. 2019)
  • Sampling and Reconstruction of Sparse Signals (23-24 Sept. 2019)

Semestre de PRIMAVERA / SPRING semester

 

Semestre de OTOÑO / FALL semester

 

Optical communications

Prof. Dr. Steffen Lochmann (University of Wismar, Germany)

Table of contents:

  • Part 1: Fundamentals of optical Fibre Transmission
  • Part 2: Beam Propagation Method (BPM): a versatile CAD-Toll for simulations optical components
  • Part 3: With high speed optical fibre networks and slow light into the photonic century

Date and time:

Thursday 17 and Friday 18 October 2019, 15:30h to 17:30h (4 hours).

Room:

Sala de Grados (Room A3004).

Language:

English.

Registration:

sca.etsist@upm.es

Workload for attendants with certificate of achievement (*):

  • Students of the PhD Program in Systems and Services for the Information Society: 5 hours' worth of "specific seminars".

  • Undergraduate students: 0.5 ECTS.

Additional information:

 

 

Image and Video Coding

Dr.-Ing. Henryk Richter (University of Rostock, Germany)

  • Introduction/Fundamentals
  • Video Compression Basics including MPEG-1 to MPEG-4
  • H.264/AVC video compression
  • H.265/HEVC video compression
  • Alternative approaches
There will be some flexibility in the contents of this seminar depending on prior knowledge of attendants (i.e. either basics or more recent advances in the field).

Date and time:

Wednesday 25 and Thursday 26 September 2019, 15:30 to 17:30.

Room:

Sala de Grados (Room A3004).

Language:

English.

Registration:

sca.etsist@upm.es

Workload for attendants with certificate of achievement (*):

  • Students of the PhD Program in Systems and Services for the Information Society: 5 hours' worth of "specific seminars".

  • Undergraduate students: 0.5 ECTS.

Additional information:

 

 

Sampling and Reconstruction of Sparse Signals

Dr.-Ing. habil. Volker Kühn (University of Rostock, Germany)

State-of-the Art:

In the last two decades the pervasion of our daily life by communications and sensing grows at increasing speed leading to the vision called Internet of Things (IoT). Moreover, mobile radio communications enters the area of industrial automation (Industrie 4.0) characterized by massive machine to machine communications. The fusion of physical processes, sensing, communication and data processing requires a proper adjustment of all parts of the processing chain. In order to keep storage and data rate requirements at a moderate level, compression is an inevitable part of digital systems. It removes redundant parts from the signal and represents these signals with as few bits as possible. Thereby, lossy and lossless compression are distinguished. We call compressible signals as being sparse in a certain domain. Conventional strategies first sample the analog signal at high rate according to Shannon's famous sampling theorem and perform compression afterwards. The technological challenge w.r.t. sampling rate and algorithmic complexity is on the encoder side while the decoder is simple and standardized.

New Approaches:

This provokes the question why sampling itself cannot directly perform the compression in order to avoid costly sampling at high rate. In order to answer this question, the lectures will first revisit Shannon's famous sampling theorem. Next, we will discuss two new approaches. First, the class of analog Finite Rate of Innovation (FRI) signals will be introduced which can be sampled at rates much lower than stated by Shannon. For reconstruction, the annihilating filter as one example of spectral estimation algorithms will be presented. Second, a technique called 'Compressed Sensing' will be explained allowing to compress sparse signals in a very efficient way. After discussing some toy examples to illustrate the underlying principle, the compression and its fundamental properties are discussed. Next, the reconstruction step is explained for one simple exemplary algorithm, the Orthogonal Matching Pursuit (OMP) algorithm. In contrast to conventional compression techniques, e.g. MP3, MPEG or H.265 for multimedia applications, the complexity is shifted from the encoder which becomes very simple to the decoder.

Date and time:

Monday 23 and Tuesday 24 September 2019, 15:30 to 17:30.

Room:

Sala de Grados (Room A3004).

Language:

English.

Registration:

sca.etsist@upm.es

Workload for attendants with certificate of achievement (*):

  • Students of the PhD Program in Systems and Services for the Information Society: 5 hours' worth of "specific seminars".

  • Undergraduate students: 0.5 ECTS.

Additional information:

 

 

 

Semestre de PRIMAVERA / SPRING semester