Random Signals for Communications and Signal Processing

Random Signals for
Communications and
Signal Processing


Pham Van Tuan
Electronic & Telecommunication Engineering
Danang University of Technology
Course Administration
!  The prerequisite of this course:
"  Linear Systems Theory in Discrete and Continuous Time
"  Basic Signals in Discrete and Continuous Time
"  Differential and Integral Calculus
"  Principles of Engineering Statistics
"  Principles of Probability
"  Facility with MATLAB
!  Goals:
"  To learn the techniques of applied probability and statistical signal
processing and apply to communication and signal processing.
!  Credits: 5
!  Grading: hw (20%); lab (20%); midterm (20%); final exam (30%); final
project (10%)
!  Contents:
"  Discrete-Time Random Process
"  Signal Modeling
"  Wiener Filters
"  Spectrum Estimation
"  Adaptive Filters
"  Applications in Communications and Signal Processing
!  Textbook:
"  M. H. Hayes, Statistical Digital Signal Processing and Modeling,

John Wiley, 1996.
"  John A. Gubner, Probability and Random Processes for Electrical
and Computer Engineering, Cambridge Uni. Press, 2006
"  Peter Vary, Digital Speech Transmission, Wiley, 2006.
!  Course reference:
"  Alle-Jan van der Veen and Geert Leus, ET4235: DIGITAL
SIGNAL PROCESSING, 2011.
Course Materials
!  At the end of this course, students will be able to:
"  Calculate the probability of combinations of events using hand and
computer analysis.
"  Write computer (MATLAB) programs to compute many probability
distributions.
"  Solve for the distributions of random variable arising from certain
functions of random variables.
"  Model datasets arising in communications using common
probabilistic models.
"  Analyze the effect of randomness on communication signals.
"  Model and analyze the linear systems using multivariate Gaussian
distributions.
"  Design statistical signal processing systems for communications
applications.
Learning Objectives