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During 2021 we will continue to support students who need to study remotely due to the ongoing impacts of COVID-19 and travel restrictions. Make sure you check the location code when selecting a unit outline or choosing your units of study in Sydney Student. Find out more about what these codes mean. Both remote and on-campus locations have the same learning activities and assessments, however teaching staff may vary. More information about face-to-face teaching and assessment arrangements for each unit will be provided on Canvas.

Unit of study_

ELEC9305: Digital Signal Processing

This unit aims to teach how signals are processed by computers. It describes the key concepts of digital signal processing, including details of various transforms and filter design. Students are expected to implement and test some of these ideas on a digital signal processor (DSP). Completion of the unit will facilitate progression to advanced study in the area and to work in the industrial use of DSP. The following topics are covered. Review of analog and digital signals. Analog to digital and digital to analog conversion. Some useful digital signals. Difference equations and filtering. Impulse and step response of filters. Convolution representation of filters. The Z-transform. Transfer functions and stability. Discrete time Fourier transform (DTft) and frequency response of filters. Finite impulse response (FIR) filter design: windowing method. Infinite impulse response (IIR) filter design: Butterworth filters, Chebyshev filters, Elliptic filters and impulse invariant design. Discrete Fourier Transform (Dft): windowing effects. Fast Fourier Transform (Fft): decimation in time algorithm. DSP hardware.

Details

Academic unit Electrical and Information Engineering
Unit code ELEC9305
Unit name Digital Signal Processing
Session, year
? 
Semester 1, 2020
Attendance mode Normal day
Location Camperdown/Darlington, Sydney
Credit points 6

Enrolment rules

Prohibitions
? 
ELEC5736
Prerequisites
? 
None
Corequisites
? 
None
Assumed knowledge
? 

Specifically the following concepts are assumed knowledge for this unit: familiarity with basic Algebra, Differential and Integral Calculus, continuous linear time-invariant systems and their time and frequency domain representations, Fourier transform, sampling of continuous time signals.

Available to study abroad and exchange students

No

Teaching staff and contact details

Coordinator Craig T Jin, craig.jin@sydney.edu.au
Type Description Weight Due Length
In-semester test Practical Exam
Programming
30% Week 13 Two hours
Outcomes assessed: LO2 LO4 LO3
In-semester test Theory Exam
Theory
30% Week 13 Two hours
Outcomes assessed: LO1 LO5 LO4 LO3
Presentation Teamwork Portfolio
10% Week 13 n/a
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6
Assignment group assignment Something Awesome Portfolio
10% Week 13 n/a
Outcomes assessed: LO1 LO5 LO4 LO3 LO2
Assignment group assignment Tutorial Portfolio
10% Week 13 n/a
Outcomes assessed: LO1 LO6 LO5 LO4 LO3
Assignment group assignment Lab Portfolio
10% Week 13 n/a
Outcomes assessed: LO2 LO3 LO4 LO5 LO6
group assignment = group assignment ?
  • Tutorials: Tutorials will include analytical problem solving sessions on the material covered in the lectures and computer aided solution/illustration. The tutorial assessment scheme requires preparation work and aims to enhance your communication skills. The solutions for the tutorials and computer codes will be available from the unit of study web page after the session. 
  • Labs: Laboratories are designed to introduce you to the DSP hardware and give you some experience in report writing. They require you to do some design, make measurements and perform demonstrations. You need to submit a brief written lab report (worth 3%) for at least one of three labs. Your best lab report mark will be counted towards the final assessment. 
  • Project: Project will require you to design and test a simple DSP system, write a report and do the demonstration of your work. It is optional and worth a bonus mark of 10% (however, if you end up with a total mark of over 100 for the unit then it will be rounded down to 100). It is expected that you would enjoy the challenge.
  • Midterm exam: The midterm exam is scheduled to provide you an assessment halfway through the semester and more importantly to give you a practice run for the final exam. It will be of the same format as the final exam (but of shorter duration). Again the solutions will be available on the unit of study web page after the exam. Both the midterm exam and the final exam will be based on the lecture material and tutorials. Both exams will be closed book and closed notes. They will test your conceptual understanding of the material. Any complex formulae needed, will be provided on the question paper.
  • Critical self-reflection essay: The critical self-reflection essay helps you to identify your strengths and weaknesses and thus take charge of your learning.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Special consideration

If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.

Academic integrity

The Current Student website provides information on academic honesty, academic dishonesty, and the resources available to all students.

The University expects students and staff to act ethically and honestly and will treat all allegations of academic dishonesty or plagiarism seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic dishonesty. If such matches indicate evidence of plagiarism or other forms of dishonesty, your teacher is required to report your work for further investigation.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to digital signal processing Lecture (2 hr) LO1 LO3 LO4 LO5 LO6
Week 02 Discrete time Fourier transform and Z-transform Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
Discrete time Fourier transform and Z-transform Computer laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Week 03 Z-transform and Sampling Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
Z-transform and Sampling Computer laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Week 04 Discrete Fourier transform and Convolution Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
Discrete Fourier transform and Convolution Computer laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Week 05 Fast Fourier Transform Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
Fast Fourier transform Computer laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Week 06 Spectral analysis using the DFT Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
Spectral analysis using the DFT Computer laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Week 07 Resampling Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
Resampling Computer laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Week 08 Polyphase decomposition and filter banks Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
Polyphase decomposition and filter banks Computer laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Week 09 ADC/DAC Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
ADC/DAC Computer laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Week 10 Transform analysis and phase response Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
Transform analysis and phase response Computer laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Week 11 Structures for discrete-time systems and quantization Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
Structures for discrete-time systems and quantization Computer laboratory (2 hr) LO2 LO3 LO4 LO5 LO6
Week 12 Filter Design Lecture and tutorial (4 hr) LO1 LO3 LO4 LO5 LO6
Filter Design Lecture and tutorial (2 hr)  

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

  • Joyce Van de Vegte, Fundamentals of Digital Signal Processing (first). Prentice Hall, 2002. 0130160776.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University’s graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. Demonstrate mastery of analytical and mathematical skills related to signal processing. These skills include convolutions, transforms, spectral analyses, linear difference equations, filters, correlation and covariance, rudimentary information theory.
  • LO2. Demonstrate proficiency in developing signal processing software to solve signal processing problems and tasks. These include spectral analyses, filtering, inverse filtering, resampling, signal modelling, deep learning for signals.
  • LO3. Plan, design and review signal processing systems
  • LO4. Apply diverse strategies to develop and implement innovative ideas in signal processing systems.
  • LO5. Present compelling oral, written, and graphic evidence to communicate signal processing practice.
  • LO6. Contribute as an individual to a team to deliver signal processing related projects.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9
Modified learning outcomes, assessment, and learning activities.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.