Note: This is an archived Handbook entry from 2015.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2015:Semester 2, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 36 hours of lectures (3 x one hour lectures per week) and up to 24 hours of workshops |
Total Time Commitment:
The prerequisite for this subject is:
Study Period Commencement:
Study Period Commencement:
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Anti-requisite for this subject is:
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For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website: http://www.services.unimelb.edu.au/disability/
CoordinatorProf Erik Weyer
Assoc Prof Erik Weyer
This subject provides an introduction to the fundamental theory of time domain and frequency domain representation of signals and discrete time linear time invariant dynamical systems, and how this theory is used to analyse and design digital signal processing systems and algorithms. Topics include:
Sampling of continuous time signals, Design of anti-aliasing filters, Time and frequency representation of discrete time signals and discrete time linear time invariant systems, Discrete Time Fourier Transform and z-transform and their properties, Low order lowpass, highpass, bandpass, bandstop filters, All-pass filter, Design of IIR filters using the bilinear transformation, Design of FIR filters with linear phase using windowing techniques and the Parks McClelland method, Discrete Time Fourier transform and its properties, Fast Fourier Transform, The use of the DFT in implementation of linear filtering algorithms, Up-sampling and down-sampling, multistage and computationally efficient implementations of up-samplers and down-samplers, Energy and power spectra for deterministic signals.
INTENDED LEARNING OUTCOMES (ILO)
Having completed this unit the student should be able to:
Hurdle requirement: Students must pass the written exam to pass the subject.
Intended Learning Outcomes (ILOs) 1 and 2 are assessed in all components. ILOs 3 and 4 are assessed in the continuous assessment.
The examination paper will consist of problems designed to test whether the student has understood the fundamental principles and acquired the ability to apply these principles to the solutions of design and estimation problems. The workshop reports can be produced much more quickly than a crafted essay, and they are expected to have a lighter weighting than an essay of similar length.
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This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
Credit may not be obtained for both
ELEN30008(431-335) Signal Processing 1 and ELEN90058 Signal Processing
LEARNING AND TEACHING METHODS
The subject will be delivered through a combination of lectures and workshops. Students will complete three workshops and one Matlab based project with the focus on design and implementation of digital signal processing systems which will reinforce the material covered in the lectures. The students will be given 11 problem sheets with tutorial like questions.
INDICATIVE KEY LEARNING RESOURCES
Students will have access to lecture notes and lecture slides. There is a prescribed text book and two alternative text books which covers the same material. In the lecture notes there are clear section references to all three textbooks. The students will be provided with fully worked solutions to all problem sheets. Matlab demonstration programs used in the lectures are available via LMS.
CAREERS / INDUSTRY LINKS
An industry representative will give a one hour lecture about industrial applications of signal processing.
B-ENG Electrical Engineering stream |
Master of Engineering (Electrical with Business)
Master of Engineering (Electrical)
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