Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Elec Engineering & Comp Science School
Advanced digital filtering: polyphase, multirate, all-pass, lattice and IIR filters. Signal conditioning, analogue filter types, sigma delta converters. Fast algorithms; Cooley-Tukey FFT, mixed radix formulations, Good-Thomas algorithm. Autoregressive, moving average signals. DSP applications and programming.
This course is an introduction to the exciting and rapidly advancing field of digital signal processing. These daysᅠDigital Signal Processing has largely replaced analog electronics for virtually all applications.ᅠDSP technology levers off computer hardware that becomes cheaper and faster every year, so a DSP solution will invariably replace analog solutions over time.ᅠ The course will be delivered in a practical manner and students will be asked to code algorithms in Matlab to demonstrate deep and practical understanding of the course material.ᅠDSP research strengths at UQ will be highlighted and applications of DSP in commodity devices such as CD and DVD players will be used as course examples.
Course Changes in Response to Previous Student Feedback
Course was rated highly by students last year so no significant changes were necessary. The exam will be invigilated and identity verified as it will be a traditional paper exam on-campus. Some modules on deep learning will be added due to the impact of this technology on modern DSP.
Course requirements
Assumed background
Some basic knowledge of Fourier Transforms, Signals, and Systems is assumed. MATLAB will be used for DSP assignments.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
ELEC3004
Recommended prerequisites
We recommend completing the following courses before enrolling in this one:
CSSE3010
Incompatible
You can't enrol in this course if you've already completed the following:
ELEC3600 or ELEC4600 or ELEC7462 or ELEC7601 or ELEC760
Course contact
Course coordinator
Course staff
Lecturer
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
It is expected that upon successful completion of the course, students will haveᅠdeveloped the ability to code and understand advanced Digital Signal Processing algorithms.ᅠ The ability to code well-known Digital Signal Processing algorithms reinforces a solid understanding of the algorithms and gives the student a solid skill base for their future career.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Implement Digital Signal Processing algorithms in MATLAB
LO2.
Use and apply data windowing appropriately to solve a range of filtering and analysis problems
LO3.
Code fundamental DSP algorithms such as the FFT and multi-rate filters
LO4.
Be able to describe the DSP processing chain of DSP-based devices such as a CD player
LO5.
Acquire an international perspective on the field through the advanced topics delivered by guest lecturers and recognized researchers
Assessment
Assessment summary
Category | Assessment task | Weight | Due date |
---|---|---|---|
Tutorial/ Problem Set | Assignment 1 | 13% |
16/08/2024 4:00 pm |
Tutorial/ Problem Set | Assignment 2 | 13% |
13/09/2024 4:00 pm |
Tutorial/ Problem Set | Assignment 3 | 14% |
25/10/2024 4:00 pm |
Examination |
Final Exam
|
60% |
End of Semester Exam Period 2/11/2024 - 16/11/2024 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Assignment 1
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 13%
- Due date
16/08/2024 4:00 pm
- Learning outcomes
- L01, L05
Task description
Convolution
Submission guidelines
Electronic submission via Blackboard using Gradescope
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Marked assignments with feedback and/or detailed solutions will be released to students within 14-21 days where the earlier time frame applies if no extensions.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Assignment 2
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 13%
- Due date
13/09/2024 4:00 pm
- Learning outcomes
- L01, L02
Task description
Filtering
Submission guidelines
Electronic submission via Blackboard using Gradescope
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Marked assignments with feedback and/or detailed solutions will be released to students within 14-21 days where the earlier time frame applies if no extensions.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Assignment 3
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 14%
- Due date
25/10/2024 4:00 pm
- Learning outcomes
- L01, L03, L04
Task description
FFT
Submission guidelines
Electronic submission via Blackboard using Gradescope
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Marked assignments with feedback and/or detailed solutions will be released to students within 14-21 days where the earlier time frame applies if no extensions.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Final Exam
- Hurdle
- Mode
- Written
- Category
- Examination
- Weight
- 60%
- Due date
End of Semester Exam Period
2/11/2024 - 16/11/2024
- Learning outcomes
- L03, L04
Hurdle requirements
Students must attain at least 40% in the final exam to be awarded a grade of 4 or more in the course.Exam details
Planning time | 10 minutes |
---|---|
Duration | 120 minutes |
Calculator options | (In person) Casio FX82 series or UQ approved , labelled calculator only |
Open/closed book | Closed Book examination - specified written materials permitted |
Materials | One A4 sheet of handwritten notes , single sided, is permitted |
Exam platform | Paper based |
Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
Grade | Cut off Percent | Description |
---|---|---|
1 (Low Fail) | 0 - 19 |
Absence of evidence of achievement of course learning outcomes. |
2 (Fail) | 20 - 44 |
Minimal evidence of achievement of course learning outcomes. |
3 (Marginal Fail) | 45 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes |
4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. |
5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. |
6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. |
7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Additional course grading information
Partial marks may be awarded to incomplete answers to problem solving questions.
Each passing grade subsumes and goes beyond the grades lower than it. At the discretion of the course coordinator, final grades may be scaled upwards but not decreased.
Students must attain at least 40% in the final exam to be awarded a grade of 4 or more in the course. If less than 40% is obtained, grade is capped at 3.
Grades are calculated based on 100% mark that is comprised of : Assignment 1 (13%) + Assignment 2 (13%) + Assignment 3 (14%) + Final Exam (60%)
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Use of AI Tools
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Having Troubles?
If you are having difficulties with any aspect of the course material you should seek help. Speak to the course teaching staff.
If external circumstances are affecting your ability to work on the course, you should seek help as soon as possible. The University and UQ Union have organisations and staff who are able to help, for example, UQ Student Services are able to help with study and exam skills, tertiary learning skills, writing skills, financial assistance, personal issues, and disability services (among other things).
Complaints and criticisms should be directed in the first instance to the course coordinator. If you are not satisfied with the outcome, you may bring the matter to the attention of the School of EECS Director of Teaching and Learning.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
Learning period | Activity type | Topic |
---|---|---|
Multiple weeks From Week 1 To Week 13 |
Lecture |
Lecture Series Covers required information on Digital Signal Processing Learning outcomes: L03, L04, L05 |
Multiple weeks From Week 2 To Week 13 |
Tutorial |
Tutorial/Practical in Computer Laboratory Coding DSP solutions in MATLAB to demonstrate understanding of the lecture material. Learning outcomes: L01, L02, L03 |
Additional learning activity information
Lectures
There are two hours of lectures each week. These will be delivered as live Echo260 lectures which will be also recorded and released via Blackboard:
Topics include:
Week 1: Linear Processing, DSP Operations, Sinusoids and Linear Systems, Complex Numbers and Phasors, Hetrodying, Fourier Series and Fourier Transforms
Week 2: Sines and Cosines, Hilbert Transformer, Even and Odd Functions, Fourier Symmetries, Implementation Issues, Circular Data, DFT Symmetries, Fourier Transform of Pulse, Fourier Transform of Pulse Train
Week 3: Sampling, Aliasing, Data Windowing, The Need for Windows, Vectors as Polynomials, Z Transform, Poles and Zeros, Convergence, Polynominal Approximations, Residues, FIR, IIR
Week 4: Non-Recursive Filters, Filter Design, Gibbs Effect, Windows, Sidelobes, Optimal Windows
Week 5: Windows Summary, Design Methods, Examples, Kaiser Window, Frequency Sampling Method
Week 6: Parks-McClellan Method, Minimax Design, Optimal Filters, Chebyshev Polynomials, Alternation Theorem, The Method, The Algorithm
Week 7: Types of Filter, Differentiator, Hilbert Transformer, Multi-Band, Quantization Effects
Week 8: Multirate Filtering, Resampling Filters, Polyphase Filters, Noble Identities, Downsampling, Upsampling, Digital Receiver Options, Polyphase Filter Partitions, Design Equations, Spectral Replication
Week 9: Single Rate Filtering with Polyphase Filters, White Noise Generator
Week 10: The DFT, DFT Tips and Tricks, FFT Tree, Radix 4 Cooley-Tukey Algorithm, Twiddle Factors, Radix-2 FFT, Scaling for Finite Arithmetic
Week 11: Recursive or IIR Filters, IIR Filter Structures, Linear Phase Filters, Sensitivity, Canonical Forms, Pole Sensitivity, First Order Sections
Week 12: All Pass Filter Structures, Microripple Filters, Digital Wave Filters
Week 13: Signal Conditioning, Sampling, Anti-Alias Filtering, Quantizing, Dual-Slope Converters, Flash Converters, Sigma-Delta Converters
Concepts presented in Lectures will be supported by many MATLAB Demonstrations.
These lectures will be recorded.
Tutorials/Pracs
Starting in Week 2, the following tutorial/laboratory sessions will be offered every week:
- Two hours of supervised tutorials/pracs in the computer laboratory to reinforce understanding of the course material. Active student participation is expected and students may come to any session.
- These sessions will not be recorded. So attend or you will miss out!
- Live Zoom tutorials will provide online support to the entire class. The sessions comprise help and advice on assignments for the whole class as well as one-on-one tutoring in breakout sessions.
- These sessions will be recorded.
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course: