Course Title: Digital Signal Processing (Electronic, PG)

Part A: Course Overview

Course Title: Digital Signal Processing (Electronic, PG)

Credit Points: 12.00

Course Code




Learning Mode

Teaching Period(s)


City Campus


125H Electrical & Computer Engineering


Sem 1 2006,
Sem 1 2008

Course Coordinator: Assoc. Professor Zahir Hussain

Course Coordinator Phone: +61 3 9925 1895

Course Coordinator Email:

Course Coordinator Location: 10.07.01

Pre-requisite Courses and Assumed Knowledge and Capabilities

It is preferred that you have basic knowledge in calculus, circuit theory, digital electronics, and computer programming. Students without sufficient knowledge in these topics may compensate by increasing the reading/ preparation time for this subject. It is recommended that all students read the DSP notes before attending Labs or lectures.

Course Description

This course presents DSP as a problem-solver for may applications in science and engineering where signal processing is the central part of modern digital systems. A general review of analog systems including Fourier analysis and filters will be considered first to help students with little background in signal processing. Then we consider first core topics in digital signal processing (DSP), starting with sampling theory, z-transforms, reconstruction, digital filter design techniques, applications of digital filters in various fields including control, radar, finance, bioinformatics, audio, and communications. Then we consider selected applied topics that had impact on engineering and science in the last two decades. We will consider binary signal transmission with matched filtering; Hilbert Transform and spectral efficiency in communications,; synchronization, frequency estimation and digital phase-locked loops; adaptive filtering for noise reduction and channel estimation,; single-bit processing for audio applications; time-frequency analysis for mono- and multi-component non-stationary FM signals, and the discrete cosine transform (DCT) for voice and video data compression. Case studies will be presented and a DSP hardware/ software project will be handled.

Objectives/Learning Outcomes/Capability Development

Objectives: This course will develop digital signal processing (DSP) theory and methods with the following objectives:
• to present a consistent methodology for solving engineering problems that can be formulated in terms of DSP;
• to familiarize the students with the computational and visualization capabilities of MATLAB;
• to illustrate the DSP problem-solving process through a variety of engineering examples and applications;
• to expose students to latest developments in DSP during the lectures.

Capabilities: Students will gain or improve capabilities in:
• Technical competence: students will study DSP fundamentals, signal and system analysis, DSP algorithm design, digital filter design, random signal analysis.
• Problem-solving and decision making: students will learn how to formulate engineering problems in terms of DSP tasks and how to apply DSP methods to solve practical engineering problems. A large number of practical examples and practice problems will be provided during the lectures, tutorials and laboratory work.
• Design skills: students will learn how to design signal processing algorithms and how to design analog and digital signal processing sytems.
• Communication: Students will have to provide regular written laboratory reports; the laboratory work will encourage working in groups and efficient communication and information exchange between students.
• Lifelong learning: students will learn to undertake self-directed study through a one-semester DSP project.

Outcomes: Upon successful completion of this course, students will be able to:
• Formulate engineering problems in terms of DSP tasks.
• Apply DSP problem-solving strategies to Engineering problems.
• Design and test DSP algorithms.
• Analyse digital and analog signals and systems.
• Recover information from signals.
• Encode information into signals.
• Design and simulate digital filters.
• Analyse and compare different signal processing strategies.

Overview of Learning Activities

Lectures (including Tutorials in week 12), Lab Experiments, and a Project.

Overview of Learning Resources

Lectures Notes (including Tutorials, Lab Experiments and Project Description) is available from RMIT Bookshop. MATLAB simulation software (plus all of its subject-dedicated toolboxes) is available in any computer Lab on-campus. Hardware components and a few DSP development kits are also available for students interested in DSP hardware.
The prescribed main reference is the DSP Lecture Notes (entitled “Digital Signal Processing” By: Zahir M. Hussain, 2002) which is a comprehensive reference, both theoretically and practically.
Students interested in further reading may consider the following recommended references which can be found at RMIT Library or elsewhere:
1) A. Oppenheim and R. Schafer, Discrete Time Signal Processing, Prentice-Hall, 1989.
2) G. E. Carlson, Signal and Linear System Analysis, Wiley, 1998.
3) Hwei Hsu, Signals and Systems, Schaum’s Outline Series, McGraw-Hill, 1995.
4) J. G. Proakis and D. G. Manolakis, Digital Signal Processing: Principles, Algorithms and Applications, Macmillan, 1996.

MATLAB help is the main reference to command MATLAB.

Overview of Assessment

Two-hour closed-book final examination (60%), Lab experiments (20%), Project (20%). All Formulas and Tables will be provided at the Exam.