ELEC ENG 3033 - Signal Processing
North Terrace Campus - Semester 1 - 2014
General Course Information
Course Code ELEC ENG 3033 Course Signal Processing Coordinating Unit School of Electrical & Electronic Engineering Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 5 hours per week Assumed Knowledge ELEC ENG 2007, MATHS 2201, MATHS 2202 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, image compression.
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 OutcomesAt the end of the course, students should be able to:
1. describe mathematically the process of sampling and its limitations
2. cite Nyquist’s sampling theorem and discuss its practical consequences
3. use and manipulate representations of discrete-time signals in both the time and frequency domains
4. perform convolution of discrete-time signals and understand its role in describing discrete-time, linear shift-invariant (LSI) systems
5. compute and interpret the Fourier transform for discrete-time signals
6. compute and interpret the frequency responses of discrete-time LSI systems
7. use the z-transform to describe discrete-time signals
8. apply techniques in the z-transform domain to analyse, design and implement discrete-time LSI systems
9. describe the concept of digital filtering and construct several common structures which realise discrete-time filters
10. design and implement both finite and infinite impulse discrete-time filters when provided with a canonical set of specifications
11. define the discrete Fourier transform, discuss its limitations and relations to other Fourier techniques
12. outline the concept underpinning algorithms for performing Fast Fourier transforms (FFT)
13. describe the concept of windowing and its implications in the different application contexts of spectrum estimation and discrete-time filter design
14. explain the basic concepts of stochastic signals and processes and describe their characteristics using statistical measures
15. perform basic statistical spectrum analysis and apply them to the analysis of synthetic and real- world data in MATLAB
16. implement a range of elementary signal processing techniques in MATLAB for the analysis and/or design of discrete-time signals and systems
17. combine elementary signal processing blocks in MATLAB to implement a flexible, software- defined radio demodulator to operate on a set of real-world radio signals
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) Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. 1-17 The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 10, 13, 15-17 An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 5-6, 8-10, 13, 15-17 Skills of a high order in interpersonal understanding, teamwork and communication. 15-17 A proficiency in the appropriate use of contemporary technologies. 15-17 A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. 17 An awareness of ethical, social and cultural issues within a global context and their importance in the exercise of professional skills and responsibilities. 15-17
Required ResourcesPrandoni, Paolo and Vetterli, Martin, Signal Processing For Communications, EPFL Press, 2008. Free online version: http://www.sp4comm.org/download.html
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 relies on lectures as the primary delivery mechanism for the material. Tutorials supplement the lectures by providing exercises and examples to enhance the understanding obtained through lectures. Practical work is used to provide hands-on experience for students to reinforce the theoretical concepts encountered in lectures. Continuous assessment activities provide the formative assessment opportunities for students to gauge their progress and understanding.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Activity Contact hours Workload hours Project 1 team digital radio project 1 30 Lecture 26 lectures 26 52 Tutorials 6 tutorials 6 30 Tests 2 tests 2 10 Exam 1 exam 2 30 TOTALS 37 152
Learning Activities Summary
Activity Sessions Topic Lectures 1-2 Introduction, Sampling 3 Discrete-time (DT) signals 4-6 DT linear shift invariant (LSI) systems 7-10 z-transforms: analytical tool for the analysis of DT signals and systems 11-14 Fourier analysis of DT signals and systems 15-18 DT filters – concept, structures and design 19-22 Spectral analysis of DT signals 23-26 DT stochastic signals and systems Tutorial 1 Sampling & DT signals 2 DT LSI systems 3 DT Fourier analysis 4 z-transforms & DT filters 5 Spectral analysis 6 Stochastic signals & systems Project 1 Digital radio
Specific Course RequirementsStudents are required to have access to Matlab software. This is available at various facilities such as the CATS suite or the undergraduate computer labs of the School of Electrical & Electronic Engineering. It is the individual student’s responsibility to ensure his or her access to these facilities at appropriate times is 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 activity Type Weighting Due date Learning outcomes addressed Tutorials Formative 10% Even weeks 1-16 Tests Summative 20% Weeks 5, 11 1-14 Project Formative 10% Week 12 3-6, 9-13, 15-17 Exam Summative 60% End of semester 1-14
Assessment Related RequirementsThe examination is a hurdle requirement. It is necessary to achieve at least 40% in the exam. If this is not achieved, the total course mark will be limited to a maximum of 49.
A hurdle requirement is defined by the University's Assessment for Coursework Programs policy as "...an assessment task mandating a minimum level of performance as a condition of passing the course.
If a student fails to meet a hurdle requirement (normally no less than 40%), and is assigned a total mark for the course in the range of 45-49, then the student is entitled to an offer of additional assessment of some type. The type of assessment is to be decided by the School Assessment Review Committee when determining final results. The student’s final total mark will be entered at no more than 49% and the offer of an additional assessment will be specified eg. US01. Once the additional assessment has been completed, this mark will be included in the calculation of the total mark for the course and the better of the two results will apply. Note however that the maximum final result for a course in which a student has sat an additional assessment will be a “50 Pass”.
If a student is unable to meet a hurdle requirement related to an assessment piece (may be throughout semester or at semester’s end) due to medical or compassionate circumstances beyond their control, then the student is entitled to an offer of replacement assessment of some type. An interim result of RP will be entered for the student, and the student will be notified of the offer of a replacement assessment. Once the replacement assessment has been completed, the result of that assessment will be included in the calculation of the total mark for the course.
Assessment DetailStudents are required to bring written attempts to selected problems for assessment at the fortnightly tutorial sessions. These formative assessments are based on the quality of attempts. The tutorials are worth 10% to the overall assessment.
There are two 45-minute closed book tests in the course. The tests will require students to submit short written responses to a set of questions under examination conditions. Each test will be worth 10% to the overall assessment.
The project is to be conducted throughout the semester using student-access computers such as those found in the CATS suites. Students will be organised in small teams to implement digital radio receivers in Matlab for a range of different modulation schemes. Each project team is required to submit a collaborative written report of their approach, the full set of source codes and the generated results. These deliverables will be assessed together and will be worth 10% of the overall assessment.
The exam will be a closed book examination in June. It will be worth 60% of the overall assessment.
SubmissionAll submissions to in term assessment activities are to be submitted electronically on MyUni by the specified time and date. No late submissions will be accepted. All in term assessments will have a two week turn-around time for provision of feedback to students.
Full details can be found at the School policies website:
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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This section contains links to relevant assessment-related policies and guidelines - all university policies.
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