Course Details Course Name: Digital Signal Processing Soutenance de thèse vendredi 24 novembre 2006, Lorient Course Details Course Name: Digital Signal Processing Course Code: EE3240 Course Credits: 3(3,1,0) Pre-requisite: EE3010 Instructor: Dr. Medien Zeghid Eng Mohamed El Ansi

Assesment Method Quantity (%) Quiz - 05 Homework - 05 Soutenance de thèse vendredi 24 novembre 2006, Lorient Assesment Method Quantity (%) Quiz - 05 Homework - 05 Midterm Exam(s) 2 30 Project 10 Final Exam 1 50

Course Outline 1. Introduction. Mathematical Representation of Signals. Mathematical Representation of Systems. 2. Signals and Signal Processing Characterization and Classification of Signals, Typical Signal Processing Operations , Examples of Typical Signals, Typical Signal Processing Applications, Why Digital Signal Processing?. 3. Discrete-Time Signals and Systems Discrete-Time Signals, Typical Sequences and Sequence Representation, Discrete-Time Systems, Time-Domain Characterization of LTI, Correlation of Signal 4. Digital Processing of Continuous Time Signals Sampling of Continuous-Time Signals, Sampling of Bandpass Signals, Analog Lowpass Filter Design, Anti-Aliasing Filter Design, Reconstruction Filter Design 5. Finite Length Discrete Transforms The Discrete Fourier Transform, Relation Between the Fourier Transform and the DFT, and Their Inverses, DFT Symmetry Relations, Discrete Fourier Transform Theorems 6. z-Transform Definition and Properties, Rational z-Transforms, Region of Convergence of a Rational z-Transform , The Inverse z-Transform, z-Transform Properties, The Transfer Function

Course Outline 7. LTI Discrete-Time Systems in the Transform Domain Transfer Function Classification Based on Magnitude Characteristics, Transfer Function Classification Based on Phase Characteristics , Types of linear-Phase Transfer Functions, Inverse Systems 8. Digital Filter Structures and Design Block Diagram Representation, Basic FIR Digital Filter Structures, Basic IIR Digital Filter Structures, FIR Filter Design, IIR Filter Design 9. Implement, apply and evaluate simple DSP applications in MATLAB.

COURSE OBJECTIVE Students will be able to: Understand mathematical descriptions of digital signal processing algorithms Express those algorithms as computer implementations (MATLAB)

Published by Mc Graw Hill, Isbn: Main course books Digital Signal Processing: A Computer Based Approach, foruth edition By Sanjit K. Mitra Published by Mc Graw Hill, Isbn:

Main course books Signal Processing First by James H McClellan, Ronald W. Schaffer and Mark A. Yoder. Published by Prentice Hall. Isbn: 0-13-120265-0

Some Recommended Books Understanding Digital Signal Processing by Richard G. Lyons. Theory and Application of Digital Signal Processing by Rabiner and Gold. A comprehensive, industrial-strength DSP reference book. Digital Signal Processing by Alan V. Oppenheim and Ronald W. Schafer. Another industrial-strength reference. Digital Signal Processing by William D. Stanley.

Rules of the Conduct No eating /drinking in class except water Cell phones must be kept outside of class or switched-off during class If your cell-phone rings during class or you use it in any way, you will be asked to leave and counted as unexcused absent. No web surfing and/or unrelated use of computers, when computers are used in class or lab.

Rules of the Conduct You are responsible for checking the class web page often for announcements. Academic dishonesty and cheating will not be tolerated and will be dealt with according to university rules and regulations Presenting any work, or a portion thereof, that does not belong to you is considered academic dishonesty. University rules and regulations: http://www.sau.edu.sa/emada/30/675

The requirement for attendance is 75%. Attendance Policy The requirement for attendance is 75%. Hospital reports are not accepted to fulfill the requirement for attendance less than 50% The students, who fail to fulfill the attendance requirement, will be excluded from the final exams and the grade of F will be given. Students with attendance more than 75% are eligible for participation degree