ADVANCED SIGNAL PROCESSING
ELE4ASP
2020
Credit points: 15
Subject outline
In this subject, students explore advance digital signal processing (DSP) by analysing and solving problems in real world digital signal systems. Students first study the necessary analytical DSP skills including fast Fourier transform, discrete cosine transform, spectrum analysis and digital models of speech, and then apply these tools to audio, communication systems and image processing applications by analysing and implementing linear predictive codes, polyphase filters and finite and infinite impulse response filters. This subject provides excellent exposure of DSP to students wishing to pursue a career in fields involving digital audio, communication and image processing.
School: Engineering and Mathematical Sciences (Pre 2022)
Credit points: 15
Subject Co-ordinator: Guang Deng
Available to Study Abroad/Exchange Students: Yes
Subject year level: Year Level 4 - UG/Hons/1st Yr PG
Available as Elective: No
Learning Activities: N/A
Capstone subject: No
Subject particulars
Subject rules
Prerequisites: ELE2CIR or Admission into SMELE or SMTNE
Co-requisites: N/A
Incompatible subjects: N/A
Equivalent subjects: N/A
Quota Management Strategy: N/A
Quota-conditions or rules: N/A
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Learning resources
Digital signal processing
Resource Type: Book
Resource Requirement: Prescribed
Author: Mitra, S.
Year: 2001
Edition/Volume: 2ND EDN
Publisher: MCGRAW HILL
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Melbourne (Bundoora), 2020, Semester 1, Day
Overview
Online enrolment: No
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Guang Deng
Class requirements
Laboratory ClassWeek: 10 - 22
One 2.00 hours laboratory class per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
LectureWeek: 10 - 22
Two 1.00 hour lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
TutorialWeek: 10 - 22
One 1.00 hour tutorial per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
3 assignments (equivalent to 300-words each) | N/A | N/A | No | 15 | SILO1, SILO2 |
3 laboratory tests (equivalent to 300-words each) | N/A | N/A | No | 15 | SILO2, SILO3 |
one 2-hour examinationHurdle requirement: To pass the subject, a minimum 40% mark in the examination is mandatory. | N/A | N/A | Yes | 60 | SILO2, SILO3 |
1 hour mid semester in-class written test | N/A | N/A | No | 10 | SILO1, SILO2 |