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EE 570 : Probability and Stochastic Processes

Graduate Course 

 

Office Hours :  Any time, please send an e-mail to : ebmattar@uob.edu.bh

Office No:       14-146-A

Office Location:  College of Engineering, Building 14.

Office Telephone:  ++ 973 17876286,  or  ++ 973 1787660

Course Contents:

      • Probability theory. 

      • Random variables. 

      • Deterministic and random signals. 

      • Noise as stochastic processes. Stationary and ergodic

      • processes. 

      • Spectral analysis and estimation. 

      • Gaussian, Markov and Poisson processes. 

      • Applications to performance analysis of CW communication systems. 

      • Introduction to statistical signal detection and estimation. 

      • Introduction to queuing and information theory.

      • Application to digital communication systems. 

 

Course Mark  Distribution :

 
1- Assignments   (5 total )     20  %       

2- Project  (Presentation)     10  %       

3- Midterm                            30  %       

4- Final  Exam                       40  %

 

Course Text  Book :

1- Probabilities,  Random Variables and  Random Processes.  M. O'Flynn,  1982.

2- Circuits,  Signals and Systems.    W. McC.  Siebert  (MIT Press,  1986).

3- Signals and Systems -  A.V.  Oppenheim,  A.S.  Willsky  and  I.T.  Young.
 

-  Matlab
-  Mathematica Maths Toolbox
-  Vsim 

Course Assignments (TOPICS)   :

      • Probability theory. 

      • Random variables. 

      • Deterministic and random signals. 

      • Noise as stochastic processes. Stationary and Ergodic processes. 

      • Spectral analysis and estimation. 

      • Gaussian, Markov and Poisson processes. 

      • Applications to performance analysis of CW communication systems. 

      • Introduction to statistical signal detection and estimation. 

      • Introduction to queuing and information theory.

      • Application to digital communication systems.

 

Course Assignments,  Tutorials,  Quizzes,  Labs  ( Previous years Works ):

      • Probability Theory

      • Random Variables

      • Deterministic and Random Signals

      • Noise as stochastic processes. Stationary and Ergodic Processes

      • Spectral analysis and estimation

      • Gaussian,  Markov and Poisson Processes

      • Applications to performance analysis of CW communication systems

      • Introduction to Statistical Signal Detection and Estimation

      • Introduction to Queuing and Information Theory

      • Application to Digital Communication Systems

 

 

Object Oriented Programming using Matlab (OOP):

 

Object Oriented Programming using Matlab (OOP), uses of classes (class), objects (obj) and data structure (struct) .. if you would like to use this approach in programming for this course, this will be great. This is optional, but it is always good to learn latest advanced programming tools. 

Download slides about Matlab (oop), from the Advanced MATLAB for Scientific Computing, Stanford University.  (press here to download >>> )   OOP-Matlab

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