ELEC ENG 3033 - Signal Processing

North Terrace Campus - Semester 1 - 2016

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.

  • General Course Information
    Course Details
    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
    Available for Study Abroad and Exchange Y
    Assumed Knowledge ELEC ENG 2007, MATHS 2201, MATHS 2202
    Assessment Examination, Quizzes, Tutorials and Practical
    Course Staff

    Course Coordinator: Associate Professor Brian Ng

    Course Co-ordinator & lecturer: Dr. Brian Ng
    Email: brian.ng@adelaide.edu.au
    Office: Ingkarni Wardli 3.35
    Phone: 8313 5054

    Lecturer: Assoc.Prof. Mathias Baumert
    Email: mathias.baumert@adelaide.edu.au
    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
    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    At the end of the course, students should be able to:
    1. describe the process of sampling mathematically and its limitations
    2. use and manipulate representations of discrete-time signals in both the time and frequency domains
    3. describe and confidently work with discrete-time, linear shift-invariant (LSI) systems to manipulate discrete-time signals
    4. compute and interpret the Fourier transform of discrete-time signals and frequency responses of discrete-time LSI systems
    5. apply techniques in the z-transform domain to analyse, design and implement discrete-time LSI systems
    6. design and implement both finite and infinite impulse discrete-time filters when provided with a canonical set of specifications
    7. define the discrete Fourier transform, discuss its limitations and relations to other Fourier techniques
    8. outline the concept underpinning algorithms for performing Fast Fourier transforms (FFT)
    9. explain the concept of stochastic signals and processes and describe their characteristics using statistical measures
    10. perform basic statistical spectrum analysis and apply them to the analysis of synthetic and real-world data in MATLAB
    11. implement a range of elementary signal processing techniques in MATLAB for the analysis and/or design of discrete-time signals and systems
    12. combine elementary signal processing blocks in MATLAB to implement moderately sophisticated algorithms which operate on real-world 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)
    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)
    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
    6, 10-12
    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
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    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
  • Learning Resources
    Required Resources
    Prandoni, Paolo and Vetterli, Martin, Signal Processing For Communications, EPFL Press, 2008. Free online version is available here.
    Recommended Resources
    Recommended 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 Learning
    This 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 Modes
    This 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 project on a contemporary DSP application 1 20
    Lecture 26 lectures 26 65
    Tutorials 6 tutorials 6 24
    Tests 2 tests 2 10
    Exam 1 exam 2 30
    TOTALS 37 149
    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 Contemporary DSP applications
    Specific Course Requirements
    Students 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.
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment activity Type Weighting Due date Learning outcomes addressed
    Tutorials Formative 10% Even weeks 1-9
    Tests Summative 20% Weeks 6, 11 1-9
    Project Formative 10% Week 12 1-6, 10-12
    Exam Summative 60% End of semester 1-9
    Assessment Related Requirements
    The 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 Detail
    Students 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.
    All 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 on the School website:

    Course Grading

    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.

  • Student Feedback

    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):
    - project achieved signficant learning and made a positive contribution to the learning experience. In 2016, the project will continue to be part of the course, and it will be tweaked to further broaden its appeal and usefulness. It will also be more integrated with the lecture course.
    - the part on stochastic signal processing needs improvement. Refresh the lecture contents, with greater emphasis on practical need for this material in real-world problems
  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

The University of Adelaide is committed to regular reviews of the courses and programs it offers to students. The University of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.