ELEC ENG 2104 - Digital Signal Processing
North Terrace Campus - Semester 2 - 2020
General Course Information
Course Code ELEC ENG 2104 Course Digital Signal Processing Coordinating Unit School of Electrical & Electronic Engineering Term Semester 2 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 4 hours per week Available for Study Abroad and Exchange N Prerequisites MATHS 1012 Incompatible ELEC ENG 3033 Assumed Knowledge ELEC ENG 1100 or ELEC ENG 1101, MATHS 1011 Course Description This course provides an introduction to processing of discrete-time (DT) signals. Fundamental principles of DT systems and signals, in both time and Fourier domains, are presented. These are followed by modern applications of digital signal processing (e.g telecommunications). Throughout the course, the focus is on developing techniques and algorithms for solving discrete-time signal processing problems.
Course Coordinator: Associate Professor Brian Ng
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 characteristics and transformations of discrete time signals mathematically; 2 Apply techniques in time and transform domains to the analysis and design of discrete-time systems; 3 Estimate the spectra of deterministic and stochastic signals, and appropriately interpret the information contained therein; 4 Demonstrate the ability to manipulate signals using analytical techniques and write algorithms to implement discrete-time systems; 5 Describe the techniques for signal modulation and discriminate between the different modulation schemes used in communication systems; 6 Create software using an industry standard programming environment that provides telecommunication functionality.
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)
1-6 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
1-6 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.
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, quizzes and assignments.
Learning Activities Summary
No information currently available.
Small Group Discovery ExperienceThis course does not include a Small Group Discovery Experience.
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) 5 Group Formative 2,4,6,8,10,12 1. 2. 3. 4. 5. Tests 40 Individual Summative 5,11 1. 2. 3. 4. 5. Assignments 40 Individual Formative 4, 9, 12 1. 2. 3. 4. 5. 6. Quizzes 15 Individual Summative 2,4,6,8,10,12 1. 2. 3. 4. 5. Total 100
This assessment breakdown complies with the University's Assessment for Coursework Programs Policy.
Assessment DetailAll assessment details will be provided on MyUni course page.
SubmissionSubmission details will be provided on MyUni course page.
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.
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