Random Signals for Communications and Signal Processing

The techniques of applied probability and statistical signal processing and apply to communication and signal processing.

Random Signals for Communications and Signal Processing

Pham Van Tuan

Electronic & Telecommunication Engineering

Danang University of Technology

Course Administration

n  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

n  Goals:

¨   To learn the techniques of applied probability and statistical signal processing and apply to communication and signal processing

n  Credits: 5

n  Grading: hw (20%); lab (20%); midterm (20%); final exam (30%); final project (10%)

n  Contents:

¨   Discrete-Time Random Process

¨   Signal Modeling

¨   Wiener Filters

¨   Spectrum Estimation

¨   Adaptive Filters

¨   Applications in Communications and Signal Processing

n  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

n  Course reference:

¨   Alle-Jan van der Veen and Geert Leus, ET4235: DIGITAL

SIGNAL PROCESSING, 2011

Course Materials

n  At the end of this course, students will be able to:

computer analysis

distributions

functions of random variables

probabilistic models

distributions

applications

Learning Objectives