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TU Berlin

Inhalt des Dokuments

Module: Foundations of Stochastic Processes (40256)


  • Axiomatic definition of probability: probability space
  • Equiprobable events, counting, and discrete probability
  • Random variables and cumulative distribution functions
  • Discrete random variables
  • Continuous random variables
  • Random vectors
  • Gaussian multivariate distributions and related distributions
  • Change of measure
  • Transform methods: probability generating function, characteristic function, moment generating function
  • Weak Law of large numbers, Central Limit Theorem, and large deviations
  • MMSE estimation and the orthogonality principle
  • Stochastic convergence
  • Markov Chains
  • Wide-sense stationary processes and spectral representation

Further Information

Module Components:
VL Probability and Stochastic Processes (4 LP/ 3 SWS)
UE Probability and Stochastic Processes (2 LP/ 1 SWS)
Duration of Module:
One semester (WS)
Type of examination:
Portfolio exam
Total LP:
Enrollment for exam:
Giuseppe Caire
Available to:
Elektrotechnik M.Sc.
LP = Leistungspunkte/Credits

Module Supporting Material

  • Course notes and slides in electronic form are provided
  • Literatur: Gubner, J. A. (2006). Probability and random processes for electrical and computer engineers . Cambridge University Press.

Zusatzinformationen / Extras


Schnellnavigation zur Seite über Nummerneingabe

LECTURE - Probability and Stochastic Processes

LV-Nr. 34331600 L 007
Prof. G. Caire

TUTORIAL - Probability and Stochastic Processes

LV-Nr. 34331600 L 008
Prof. G. Caire