Seminarios Avanzados de Investigación
Seminarios previstos para el curso 2017/2018.
Resumen de seminarios y fechas
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Título |
Fechas |
Profesor |
| Sampling and Reconstruction of Sparse Signals |
25-26 Sep | Prof. Dr.-Ing. Volker Kühn (University of Rostock, Germany) |
| Video Coding |
27-28 Sep | Prof. Dr.-Ing. Henryk Richter (University of Rostock, Germany) |
| Optical Communications |
19-20 Oct |
Prof. Dr. Ing. Steffen Lochmann (Hochschule Wismar, Germany) |
| IoT | 26 Oct | Keysight |
| Writing in Engineering | 14, 16, 21 y 23 Nov | Prof. Dr. Inmaculada Álvarez de Mon (UPM) |
| Mathematical methods for solving partial differential equations. Applications to engineering |
Prof. Dr. Juana Sendra (UPM), Prof. Dr. Alberto Lastra (U. Alcalá) | |
| Some recent problems on symbolic computation. Applications |
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Prof. Dr. Juana Sendra (UPM), Prof. Dr. Alberto Lastra (U. Alcalá) |
| An introduction to Maple software. Applications to engineering | Prof. Dr. Juana Sendra (UPM), Prof. Dr. Alberto Lastra (U. Alcalá) | |
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| MIMO Mobile Radio Systems | Prof. Dr.-Ing. Tobias Weber (University of Rostock, Germany) | |
| Challenges in Wireless Communications | Prof. Dr.-Ing. Andreas Ahrens (Hochschule Wismar, Germany) | |
| Last Generation of Multicore Video Decoders | Prof. Dr. Wassim Hamidouche (INSA Renns, France) | |
| Git: Basic Principles and Use |
Prof. Dr. Karol Desnos (INSA Renns, France) | |
Semestre de otoño.
Speaker:
Prof. Dr-Ing. Volker Kühn (University of Rostock, Germany)
Content
In the last two decades the pervasion of our daily life by communication and multimedia devices like smart phones, digital cameras or MP3 players grows at increasing speed. The basic foundation of all devices is digital signal processing, especially the representation of analog signals by bits and bytes. 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.
Conventional strategies first sample the analog signal at high rate according to Shannon's famous sampling theorem and compress it afterwards. This provokes the question why the sampling process itself cannot directly perform the compression in order to avoid costly sampling at high rate. In order to answer this question, the lectures will give an overview of state-of-the-art sampling techniques and will focus on two different approaches.
The first part will introduce a technique called 'Compressed Sensing' allowing to compress sparse signals in a very efficient way. After discussing some toy examples to illustrate the underlying problem, the compression and its fundamental properties are introduced. Next, the reconstruction step is explained for one simple exemplary algorithm, the Orthogonal Matching Pursuit (OMP) algorithm.
In the second part, Shannon's famous sampling theorem will be revisited first. Next, 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. Finally, this approach is applied to Particle Image Velocimetry as one possible example.
Language
English
Workload
1 ECTS
Registration
Master program secretary (A6104), Julia Barahona (actividades@etsist.upm.es)
Dates
26 and 27, September 2016
Timetable
14:30h-17:30h
Room
Aula Javier Hernández (A3005)
Additional information
Speaker
Prof. Dr-Ing. Henryk Richter (University of Rostock, Germany)
Content
Contents:
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Methods, techniques and algorithms for data compression
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Video coding standards and their specifics
Language
English
Workload
1 ECTS
Registration
Master program secretary (A6104), Julia Barahona (actividades@etsist.upm.es)
Dates
28 and 29 September 2016
Timetable
14:30h-17:30h
Room
Aula Javier Hernández (A3005)
Additional information
Introduction Compression Fundamentals (part 1)
Introduction Compression Fundamentals (part 2)
Introduction Compression Fundamentals (part 3)
Video Compression Basics MPEG1-2-4 H263
H264
H265
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Speaker: |
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Prof. Dr-Ing. Volker Kühn (University of Rostock, Germany) |
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Content |
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In the last two decades the pervasion of our daily life by communication and multimedia devices like smart phones, digital cameras or MP3 players grows at increasing speed. The basic foundation of all devices is digital signal processing, especially the representation of analog signals by bits and bytes. 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.
Conventional strategies first sample the analog signal at high rate according to Shannon's famous sampling theorem and compress it afterwards. This provokes the question why the sampling process itself cannot directly perform the compression in order to avoid costly sampling at high rate. In order to answer this question, the lectures will give an overview of state-of-the-art sampling techniques and will focus on two different approaches.
The first part will introduce a technique called 'Compressed Sensing' allowing to compress sparse signals in a very efficient way. After discussing some toy examples to illustrate the underlying problem, the compression and its fundamental properties are introduced. Next, the reconstruction step is explained for one simple exemplary algorithm, the Orthogonal Matching Pursuit (OMP) algorithm.
In the second part, Shannon's famous sampling theorem will be revisited first. Next, 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. Finally, this approach is applied to Particle Image Velocimetry as one possible example. |
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Language |
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English |
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Workload |
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1 ECTS |
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Registration |
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Master program secretary (A6104), Julia Barahona (actividades@etsist.upm.es) |
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Dates |
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26 and 27, September 2016 |
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Timetable |
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14:30h-17:30h |
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Room |
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Aula Javier Hernández (A3005) |
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Additional information |
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Speaker |
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Prof. Dr-Ing. Henryk Richter (University of Rostock, Germany) |
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Content |
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Contents:
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Language |
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English |
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Workload |
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1 ECTS |
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Registration |
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Master program secretary (A6104), Julia Barahona (actividades@etsist.upm.es) |
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Dates |
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28 and 29 September 2016 |
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Timetable |
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14:30h-17:30h |
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Room |
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Aula Javier Hernández (A3005) |
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Additional information |
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Introduction Compression Fundamentals (part 1) Introduction Compression Fundamentals (part 2) Introduction Compression Fundamentals (part 3)
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Speaker: |
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Prof. Dr. Ing. Steffen Lochmann (Hochschule Wismar, Germany) |
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Content |
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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 |
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Language |
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English |
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Workload |
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1 ECTS |
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Registration |
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Master program secretary (A6104), Julia Barahona (actividades@etsist.upm.es) |
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Dates |
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6-7, October 2016 |
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Timetable |
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14:30h-17:30h |
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Room |
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Sala de Grados (A3004) |
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Additional information |
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Lecturers: |
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Prof. Dr. Juana Sendra (UPM), Prof. Dr. Alberto Lastra (U. Alcalá) |
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Content |
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The course aims to provide introductory concepts, results, and algorithms on symbolic computation and its applications to some specific problems related to cryptography, systems of equations, differential equations, partial differential equations, etc. The basic idea of the course is to learn the new and powerful algorithms in symbolic computation and illustrate them by applications. Theoretical results will be applied to specific problems with Maple software. |
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Language |
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English |
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Workload |
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1 ECTS |
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Registration |
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Master program secretary (A6104), Julia Barahona (actividades@etsist.upm.es) |
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Dates |
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December 2016, 2nd |
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Timetable |
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15:30h-19:30h |
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Room |
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Sala de Grados (A3004), Mathematics Lab |
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Additional information |
Semestre de primavera.
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Speaker: Prof. Dr. Tobias Weber (University of Rostock) |
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Content |
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Lesson 1: Modelling of MIMO systems. (Tuesday 21th 15:30h)
In the first part of the lecture after a short introduction the modeling of MIMO systems will be introduced. The main topic of the first part of the lecture is the introduction of the information theoretical basics of MIMO systems. MIMO capacity and key techniques, i.e., waterfilling and singular value decomposition will be discussed.
Lesson 2: MIMO channel modelling. (Wednesday 22th at 15:30h)
The second part of the lecture gives an overview of MIMO channel modeling. Both more realistic geometrical and statistical channel models will be introduced.
Lesson 3: Practical MIMO system. (Thursday 23th at 15:30h)
In the third part of the lecture a bunch of practical MIMO system concepts will be discussed. The lecture will close with a short overview of diversity techniques and space time coding. |
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Language |
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English |
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Workload |
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1 ECTS |
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Registration |
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Secretaría de Programa Máster (6104), Julia Barahona (actividades@etsist.upm.es) |
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Dates |
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21, 22 and 23 March 2017 |
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Timetable |
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15:30-17:30h |
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Room |
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Salón de Grados (A3004) |
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Additional information |
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