Course Title: Digital Signal Processing
Part A: Course Overview
Course Title: Digital Signal Processing
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
EEET1123 |
City Campus |
Postgraduate |
125H Electrical & Computer Engineering |
Face-to-Face |
Sem 1 2006, Sem 1 2008, Sem 1 2009, Sem 1 2010, Sem 1 2012, Sem 1 2013, Sem 1 2014, Sem 1 2015, Sem 1 2016 |
EEET1123 |
City Campus |
Postgraduate |
172H School of Engineering |
Face-to-Face |
Sem 1 2017, Sem 1 2018, Sem 1 2020, Sem 1 2024 |
Course Coordinator: Dr Saman Atapattu
Course Coordinator Phone: -
Course Coordinator Email: saman.atapattu@rmit.edu.au
Course Coordinator Location: -
Course Coordinator Availability: By appointment
Pre-requisite Courses and Assumed Knowledge and Capabilities
Assumed Knowledge
You are expected to have sound knowledge on the following topics: signal description and analysis in time and frequency domains, Fourier/spectrum analysis, analog and digital filters, z-transforms, fundamentals of communication systems, digital modulation techniques, and signal analysis using the software tool Matlab. You are also expected to have basic computer programming skills to work on the lab exercises.
Course Description
Digital signal processing is an important aspect in the current era of communication engineering especially in wireless and mobile communication. Though deterministic signals are transmitted to communicate information in reality what we receive actually are corrupted signals that are random in nature. In this course therefore we cover random signal theories and its applications to communication engineering in order to understand the behavior of communication signals and improve the performance of communication systems by performing intelligent signal processing.
The topics covered in this course are;
- A quick recap of Discrete Fourier Transform (DFT), spectral analysis, filter design and windowing functions
- Fundamentals of random signal theory and analysis, and LTI system response to random signals
- Modelling communication signals as random processes
- Baseband signal processing, signal synthesis and filter design for communication
- Statistical signal processing in communication for signal detection and synchronization
Objectives/Learning Outcomes/Capability Development
At the postgraduate level this course develops the following Program Learning Outcomes:
- High levels of technical competence in the field.
- Be able to apply problem solving approaches to work challenges and make decisions using sound engineering methodologies
- Be able to apply a systematic engineering design approach and have strong research and design skills
Upon successful completion of this course, you will be able to:
- Analyse signals in communication systems
- Process random signals to meet a particular requirement
- Simulate, synthesize and process communication signals using software tools
- Write signal processing algorithms and methods with minimal supervision and communicate the outcomes as a written report
Overview of Learning Activities
You will be actively engaged in a range of learning activities such as pre-recorded lectures, lectorials, tutorials, and laboratories. Delivery may be face to face, online or a mix of both.
You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, andthrough links and material specific to this course that is available through myRMIT Studies Course.
The key concepts, theories, and their practical applications will be thoroughly explained in pre-recorded lecture videos. These pre-recorded lectures will encompass various case studies in the field of communication engineering.
The laboratory exercises will train students to apply the random signal theories in practical scenarios and develop skills to simulate signals and write algorithms to process signals to improve the performance of communication systems.
Overview of Learning Resources
RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course.
There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.
Overview of Assessment
This course has no hurdle requirements.
Assessment tasks
Assessment Task 1: Lab-Exam 1 Assessment Task 2: Mid-Semester Assessment Assessment Task 3: Lab-Exam 2 Assessment Task 4: End of Semester Written Test |
If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact your program Manager or Equitable Learning Services if you would like to find out more.