ELEC ENG 7079 - Principles of Signal Processing
North Terrace Campus - Semester 2 - 2018
General Course Information
Course Code ELEC ENG 7079 Course Principles of Signal Processing Coordinating Unit School of Electrical & Electronic Engineering Term Semester 2 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Contact Up to 4 hours per week Available for Study Abroad and Exchange Y Assumed Knowledge ELEC ENG 2007, MATHS 2201, MATHS 2202 or equivalent Course Description Discrete time (DT) signals; DT Linear Shift Invariant (LSI) systems; Fourier transforms; Fourier analysis for discrete time systems: DT Fourier series, DT Fourier transform, discrete Fourier transform, spectral leakage, frequency resolution, non-parametric spectral estimation. Digital filtering principles; Digital filter design; Statistical signal processing fundamentals; Practical signal processing skills in MATLAB; Applications example of digital signal processing: digital radio techniques.
Course Coordinator: Dr Brian NgCourse Co-ordinator & lecturer: Dr. Brian Ng
Office: Ingkarni Wardli 3.35
Phone: 8313 5054
Lecturer: Assoc.Prof. Mathias Baumert
Office: Ingkarni Wardli 3.31
Phone: 8313 1616
Administrative Enquiries: Office of the School of Electrical & Electronic Engineering, Room 3.26, Level 3, Ingkarni Wardli
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesOn successful completion of this course students will be able to:
1 Describe the process of sampling mathematically and articulate its benefits and limitations in modern engineering applications 2 Use and manipulate representations of discrete-time signals in both the time and frequency domains 3 Analyse and design discrete-time, linear shift-invariant (LSI) systems to manipulate discrete-time signals 4 Apply various techniques underpinned by z- and Fourier transforms for signal processing applications 5 Choose the most appropriate domain to perform processing, and switch fluidly between different domains 6 Describe the characteristics of stochastic signals and processes using statistical measures, and apply them to model real-world systems 7 Perform basic statistical spectrum analysis and apply them to the analysis of synthetic and real-world data in MATLAB 8 Write MATLAB code to perform signal processing functions in a team environment, to produce a high level product for real-world use
The above course learning outcomes are aligned with the Engineers Australia Stage 1 Competency Standard for the Professional Engineer.
The course is designed to develop the following Elements of Competency: 1.1 1.2 1.3 1.4 1.5 1.6 2.1 2.2 2.3 2.4 3.1 3.2 3.3 3.4 3.5 3.6
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
1-8 Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
1-8 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
3, 4, 6 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
4, 6 Self-awareness and emotional intelligence
- a capacity for self-reflection and a willingness to engage in self-appraisal
- open to objective and constructive feedback from supervisors and peers
- able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
Required ResourcesPrandoni, Paolo and Vetterli, Martin, Signal Processing For Communications, EPFL Press, 2008. Free online version available here.
Recommended ResourcesRecommended textbooks:
- Oppenheim, Alan V. and Schafer, Ronald W. and Buck, John R., Discrete-Time Signal Processing, 2nd edition, Prentice-Hall, 1999, ISBN: 978-0-137-54920-7.
- Proakis, John G. and Manolakis, Dimitris G., Digital Signal Processing, 4th edition, Prentice- Hall International, 2006, ISBN: 978-0-131-87374-2.
- Bose, T., Digital Signal and Image Processing, Wiley 2004, ISBN: 978-0-471-32727-1.
- Mitra, Sanjit K., Digital Signal Processing: A Computer-Based Approach, 2nd edition with DSP Laboratory using MATLAB, McGraw-Hill, 2002, ISBN 9780071226073.
- Lathi, B. P., Linear Systems and Signals, 2nd edition, Oxford University Press, 2005, ISBN: 978-0-19-515833-5.
- Gilat, A., MATLAB: An Introduction with Applications, 2nd edition, Wiley 2004, ISBN: 978-0-471-69420-5.
Online LearningThis course uses MyUni exclusively for providing electronic resources, such as lecture notes, assignment papers, sample solutions, discussion boards, strongly recommended that the students make intensive use of these resources for this course.
Link to MyUni login page: https://myuni.adelaide.edu.au
Learning & Teaching Activities
Learning & Teaching ModesThis course uses a conventional lecture/tutorial delivery of material. Students are expected to spend time outside of these to attain the learning outcomes.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.There will be up to 42 contact hours throughout the course. Students are expected to spend approximately 100 hours of private study, preparing for tutorials, tests and exams. The project component is expected to take approximately 15 hours.
Learning Activities Summary
No information currently available.
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Task Weighting (%) Individual/ Group Formative/ Summative Due (week)* Hurdle criteria Learning outcomes Tutorials (fortnightly) 10 Individual Formative Weeks 2-12 1. 2. 3. 4. 5. 6. 7. Tests 20 Individual Summative Weeks 5, 11 1. 2. 3. 4. 5. 6. Project 15 Group Formative 12 2. 3. 4. 5. 6. 7. 8. Exam 55 Individual Summative Exam Period Min 40% 1. 2. 3. 4. 5. 6. Total 100
This assessment breakdown complies with the University's Assessment for Coursework Programs Policy.
This course has a hurdle requirement. Meeting the specified hurdle criteria is a requirement for passing the course.
No information currently available.
No information currently available.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.Feedback from 2015 SELTs (plans for 2016 in italics):
- content, including Matlab, is difficult. Update tutorials to better reflect the learning needs of the class.
- Academic Support with Maths
- Academic Support with writing and speaking skills
- Student Life Counselling Support - Personal counselling for issues affecting study
- International Student Support
- AUU Student Care - Advocacy, confidential counselling, welfare support and advice
- Students with a Disability - Alternative academic arrangements
- Reasonable Adjustments to Teaching & Assessment for Students with a Disability Policy
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangement Policy
- Academic Honesty Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Elder Conservatorium of Music Noise Management Plan
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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