This document outlines the course details for a digital signal processing course. The main goal of the course is to design digital linear time-invariant filters that are widely used in applications such as audio, communications, radar, and biomedical engineering. Topics that will be covered include sampling of continuous-time signals, discrete-time signals and systems, the z-transform, filter design techniques, discrete Fourier transforms, and applications of digital signal processing. Students will be evaluated based on midterm and final exams, quizzes, assignments, and a project.

1. ‫ر‬َ‫ـد‬ْ‫ق‬‫ِـ‬‫ن‬،،،‫لما‬‫اننا‬ ‫نصدق‬ْْ‫ق‬ِ‫ن‬‫ر‬َ‫د‬
LECTURE (0)
Course Outlines
Amr E. Mohamed
Faculty of Engineering - Helwan University

2. Course Details
 Objective
 Our main goal is to be able to design digital LTI filters. Such filters are using
widely in applications such as audio entertainment systems,
telecommunication and other kinds of communication systems, radar, video
enhancement, and biomedical engineering.
 Text Book:
 “Digital Signal Processing”, E. M. Saad, S. M. Habashy.
 Grading
 Midterm:
 Quizzes: 50
 Assignments:
 Project:
 Final: 100

3. Useful References
 Reference Books
 “Discrete Time Signal Processing”, Alan V. Oppenheim and R. W. Schafer, 3rd ed., Prentice Hall, 2003.
 “Digital Signal Processing, Signals, Systems and Filters”, Andreas Antoniou, The McGraw-Hill, 2006.
 “Digital Signal Processing: Principles, Algorithms, and Applications”, Prentice Hall, 3rd Edition, John G.
Proakis, Dimitris G. Manolakis
 “Applied Digital Signal Processing: Theory and Practice”, Dimitris, G. Manolakis, Vinay K. Ingle,
Cambridge university press 2011.
 “Think DSP Digital Signal Processing in Python”, Allen B. Downey, Green Tea Press, 2014.
 “Introduction to Signal Processing and Filter Design”, B. A. Shenoi, Wiley, 2006.
 “Signal Processing First”, J. H. McClellan, R. W. Schafer, and M. A. Yoder, Prentice Hall, 2004. (suitable
for beginners)
 Web Sites
 Digital Signal Processing slides in Cambridge
• Markus Kuhn, http://www.c1.cam.ac.uk/Teaching/2005/DSP
 MATLAB Tutorial
• http://www.utexas.edu/cc/math/tutorials/matlab6/matlab6.html

4. Aims of the course
 Digital Signal Processing (DSP) is being used very widely in applications that
include telecommunication equipment, multimedia systems, electronic and
biomedical instrumentation, automotive systems and many military and weapon
systems. DSP chips, general processors or dedicated ASIC chips, are now able to
process wide bandwidth signal of all sorts in real-time. The application of DSP is
only limited by our imagination instead of DSP technology itself.
 The objectives of the course are:
1. Determine if a DSP system is linear, time-invariant, causal, and memoryless, determine
asymptotic, marginal and BIBO stability of systems given in frequency domain.
2. Perform Z and inverse Z transforms using the definitions, Tables of Standard Transforms and
Properties, and Partial Fraction Expansion.
3. Design FIR and IIR filters by hand to meet specific magnitude and phase requirements.
4. Analyze a DSP system in time and frequency domains.
5. Design and test DSP algorithms;
6. Use computers and MATLAB to create, analyze and process signals, and to simulate and
analyze systems sound and image synthesis and analysis, to plot and interpret magnitude and
phase of LTI system frequency responses.

5. Course Outline
 Introduction to Digital Signal Processing
 Review of Signals, Systems, and Fourier Transform
 Sampling of Continuous-Time Signals
 Uniform Sampling
 Frequency-Domain Representation of Sampling
 Reconstruction of a Band-limited Signal from its Samples
 Discrete-Time Signals and System
 Discrete-Time Signals: Sequences
 Discrete-Time Systems
 Linear Time-Invariant Systems
 Properties of Linear Time-Invariant Systems
 Linear Constant-Coefficient Difference Equations
 Freq. Domain Representation of Discrete-Time Signals
 Representation of Sequences by Fourier Transforms
 Symmetry Properties of the Discrete Time Fourier Transform

6. Course Outline (Cont.)
 The Z-Transform
 Z-Transform
 Properties of the Region of Convergence of the z-Transform
 The Inverse Z-Transform
 Z-Transform Properties
 Transform Analysis of Linear Time-Invariant Systems
 The Frequency Response of LTI Systems
 Constant-Coefficient Difference Equations
 Frequency Response for Rational System Functions
 Relationship between Magnitude and Phase
 All-Pass Systems
 Minimum-Phase Systems
 Filter Design Techniques
 Design of FIR Filters by Windowing
 Optimum Approximation of FIR Filters
 Design of Discrete-Time IIR Filters from Continuous-Time Filters

7. Course Outline (Cont.)
 Structures for Discrete-Time Systems
 Block Diagram Representation
 Signal Flow Graph Representation
 Basic Structures for IIR Systems
 Transposed Forms
 Basic Structures for FIR Systems
 Finite Precision Numerical Effects
 Effects of Coefficient Quantization
 Effects of Round-Off Noise in Digital Filters
 Computation of the Discrete-Fourier Transform
 The Discrete Fourier Transform (DFT)
 Properties of the DFT
 Fast Fourier Transform (FFT)
 Zero Padding
 Circular Convolution
 Applications of Digital Signal Processing

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