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Course

COM-300: Stochastic models in communication

Summary

L'objectif de ce cours est la maitrise des outils des processus stochastiques utiles pour un ingénieur travaillant dans les domaines des systèmes de communication, de la science des données et de l'informatique.

Lectures

Instructor

Patrick Thiran

Patrick Thiran is a full professor in network and systems theory at the School of Computer and Communication Sciences at EPFL. He holds an electrical engineering degree from the Université Catholique de Louvain, Louvain-la-Neuve, Belgium, an M.Sc. degree in electrical engineering from the University of California at Berkeley, USA, and he received the PhD degree from EPFL, in 1996. He became an adjunct professor in 1998, an assistant professor in 2002, an associate professor in 2006 and a full professor in 2011. He was with Sprint Advanced Technology Labs in Burlingame, California, in 2000-01. His research interests are in communication and social networks, performance analysis and stochastic models. He is currently active in the analysis and design of wireless and PLC networks (scaling laws, medium access control), in network monitoring (network tomography, multi-layer networks), and data-driven network science. He also contributed to network calculus and to the theory of locally coupled neural networks and self-organizing maps. He served as an associate editor for the IEEE Transactions on Circuits and Systems in 1997-99 and for the IEEE/ACM Transactions on Networking in 2006-10. He is currently on the editorial board of the IEEE Journal on Selected Areas in Communication. He is/was on the program committee of different conferences in networking, including ACM Sigcomm, Sigmetrics, IMC, CoNext and IEEE Infocom. He was TPC chair of AMC IMC 2011 and CoNext 2012. He is a Fellow of the Belgian American Educational Foundation and of the IEEE. He received the 1996 EPFL Doctoral Prize and the 2008 Crédit Suisse Teaching Award.

Official source

Moodle Page

http://go.epfl.ch/COM-300

Summary

Lectures

Instructor

Patrick Thiran

Official source

Moodle Page

http://go.epfl.ch/COM-300

Ontological neighbourhood

Mathematics

Analysis: Differential anaysis

Probability theory: Topics in probability theory

Algebra: Linear algebra

Statistics

Statistical inference: Mathematical statistics, Bayesian inference

Information engineering

Signal processing: Fourier analysis

Artificial intelligence: Computer vision

Lectures in this course (31)

Stochastic Models for Communications Log in to Mediaspace to watch this video

Covers stochastic models for communications and the estimation of correlation functions.

Application: Error Rate of PAM Signal Log in to Mediaspace to watch this video

Explores the impact of noise on signal transmission and the calculation of error rates in communication systems.

Stochastic Models for Communications Log in to Mediaspace to watch this video

Covers stochastic models for communications, including Poisson processes and counting processes.

Superposition and Decomposition Log in to Mediaspace to watch this video

Explains superposition and decomposition of signals into simpler components.

Stochastic Models for Communications Log in to Mediaspace to watch this video

Covers stochastic models for binary transmission in communications systems.

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