• Class Number 6974
  • Term Code 3260
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Dr Prasanga Samarasinghe
    • Dr Huiyuan Sun
  • Class Dates
  • Class Start Date 25/07/2022
  • Class End Date 28/10/2022
  • Census Date 31/08/2022
  • Last Date to Enrol 01/08/2022
    • Jiarui Wang
    • Shaoheng Xu
SELT Survey Results

Digital Signal Processing (DSP) has become over the years an important tool with applications in Electrical and Mechanical Engineering fields. DSP has penetrated many domains of applications, such as digital communications, medical imaging, audio & video systems, consumer electronics, robotics, remote sensing, finance, etc.

The Discrete-Time Signal Processing paradigm is a convenient setting to analyse the basic principles of DSP. At the end of this course, the students should be able to understand these basic principles, and apply fundamental algorithms and methods to analyse and design discrete- time systems for modern DSP applications. Though the course will focus on the study of theoretical concepts, methods and algorithms, the student will be confronted with application and implementation issues, through various examples and assignments requiring personal computer work including processing of real-world signals.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Analyse and evaluate the properties of LTI systems in terms of its z-transforms.
  2. Understand the sampling theorem and perform sampling on continuous-time signals by applying advanced knowledge of the sampling theory (i.e., aliasing, quantisation errors, pre-filtering).
  3. Apply the concepts of all-pass and minimum-phase systems to analyse the LTI system and address complex design problems.
  4. Evaluate design problems related to frequency selective processing and design FIR/IIR filters.
  5. Construct systems for spectral estimation of real signals by applying advanced knowledge of Fourier techniques.
  6. Judge implementation aspects of modern DSP algorithms.
  7. Apply the relevant theoretical knowledge to design and analyse a practical discrete-time signal system, such as a radar or audio system, using Matlab platform.
  8. Investigate advanced signal processing techniques and implement complicated systems based on the course material.

Examination Material or equipment

Calculator (non-programmable)

Recommended Textbook: A.V. Oppenheim & R.W. Schafer, “Discrete-Time Signal Processing”, New International Edition (3e), Pearson, 2013. 

Another useful resource is the MIT open Courseware: http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-341-discrete-time-signalprocessing-fall-2005/

Staff Feedback

Students will be given feedback in the following forms in this course:

  • written comments
  • verbal comments
  • feedback to whole class

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

Textbook Chapters

The chapters 2-10 will be covered except for the content being covered by ENGN2228 and other materials. The course will include the following contents:

  • Chapter 2: 2.0-2.9
  • Chapter 3: 3.0-3.7
  • Chapter 5: 5.0-5.7.1
  • Chapter 4: 4.0-4.6 and 4.8
  • Chapter 8: 8.0-8.7
  • Chapter 6: 6.0-6.5 and 6.7-6.8
  • Chapter 9: 9.0-9.5
  • Chapter 7: 7.0-7.5
  • Chapter 10: 10.0-10.3

Class Schedule

Week/Session Summary of Activities Assessment
1 Course Introduction. Fourier Transform of discrete-time signals.
2 Fourier Transform of discrete-time signals. z-Transforms.
3 z-Transforms. Tutorial quiz 1 due
4 Transform Analysis of LTI systems. Tutorial quiz 2 due, tutorial quiz 1 mark release, DSP project release
5 Transform Analysis of LTI systems. Sampling of continuous time signals. Tutorial quiz 3 due, tutorial quiz 2 mark release
6 Sampling of continuous time signals. DFT. Tutorial quiz 4 due, tutorial quiz 3 mark release. Mid-term exam.
7 DFT. Tutorial quiz 5 due, tutorial quiz 4 mark release
8 Structure of Systems. Tutorial quiz 6 due, tutorial quiz 5 mark release
9 Guest Lecture 1. FFT Algorithms. Tutorial quiz 7 due, tutorial quiz 6 mark release
10 Guest Lecture 2. Filter Design Techniques. Tutorial quiz 8 due, tutorial quiz 7 mark release
11 Filter Design Techniques. Fourier Analysis of Real Signals with DFT. Tutorial quiz 9 due, tutorial quiz 8 mark release DSP project due on Friday
12 Fourier Analysis of Real Signals with DFT. Course Review. Tutorial quiz 10 due, tutorial quiz 9 mark release DSP project mark release on Friday
13 Examination. Tutorial quiz 10 mark release. Final examination

Tutorial Registration

Registration information available on Wattle

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Weekly Quiz 10 % * * 1,2,3,4
Mid-term Exam 20 % * * 1,2,3
DSP Project 30 % 21/10/2022 28/10/2022 2,4,5,6,7,8
Final Examination 40 % * * 1,2,3,4,5,6

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Assessment Task 1

Value: 10 %
Learning Outcomes: 1,2,3,4

Weekly Quiz

Starting in Week 3, tutorials will include an in-class quiz, based on course topics and question set from the previous week. Typically, the quiz should take around 5-10 minutes. Students finish and submit the answer at the tutorial. Each quiz is worth 1% and there is a total of 10 quizzes. 

Value: 10%

Assessment Task 2

Value: 20 %
Learning Outcomes: 1,2,3

Mid-term Exam

Exam Content: More information will be given closer to the mid-term exam.

Permitted Materials: Calculator (non-programmable).

Note: All major equations and tables will be provided in the mid-term exam. A summary sheet will be given closer to the mid-term exam.

Value: 20%

Assessment Task 3

Value: 30 %
Due Date: 21/10/2022
Return of Assessment: 28/10/2022
Learning Outcomes: 2,4,5,6,7,8

DSP Project

This assessment requires students to apply DSP to audio or radar applications using Matlab. It is designed for applying advanced theoretical knowledge on practical systems, developing critical analysis ability, and transmitting solutions to complex problems. For postgraduate students, this project has extra assessment components to demonstrate autonomy and adaptability as a learner through investigating advanced signal processing techniques and implementing complicated systems based on the course material. Students have to score a minimum of 50% to pass this assessment.

Value: 30%

Assessment Task 4

Value: 40 %
Learning Outcomes: 1,2,3,4,5,6

Final Examination

The final exam will cover all lecture material, plus all the tutorial and quiz questions.

Exam Structure: More information will be given closer to the final exam.

Permitted Materials:

  • Calculator (non-programmable).
  • One A4 page with notes on both sides.

Note: A summary sheet will be given closer to the exam.

Value: 40%

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.


The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Dr Prasanga Samarasinghe

Research Interests

Dr Prasanga Samarasinghe

Dr Huiyuan Sun

Research Interests

Audio Signal Processing (Microphone and Loudspeaker arrays, Spatial audio recording and reproduction, Noise cancellation and Room acoustics)

Dr Huiyuan Sun

Friday 13:30 14:30

Research Interests



Research Interests


Jiarui Wang

Research Interests

Jiarui Wang

Shaoheng Xu

Research Interests

Shaoheng Xu

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions