Advanced Signal Processing

Subject ELEN90052 (2011)

Note: This is an archived Handbook entry from 2011.

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2011:

Semester 1, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 36 hours of lectures and up to 24 hours of workshops
Total Time Commitment: 120 hours

Prerequisites for this subject are:

ELEN90058 Signal Processing ( prior to 2011, ELEN30008 Signal Processing 1)

ELEN90054 Probability and Random Models( prior to 2011, ELEN30002 Stochastic Signals and Systems )

Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects: Anti-requisite for this subject is:
Core Participation Requirements: 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:


Prof Subhrakanti Dey


Subject Overview:
This subject provides an in-depth introduction to statistical signal processing. Students will study topics including:
  • Applications of statistical signal processing;
  • A review of stochastic signals and systems fundamentals – random processes, white noise, stationarity, auto- and cross-correlation functions, spectral- and cross-spectral densities, properties of linear time-invariant systems excited by white noise;
  • Parameter estimation - least squares and its properties, recursive least squares and least mean squares, optimisation-based methods, maximum likelihood methods;
  • Kalman filtering and selected topics from spectral estimation, Wiener and Markov filtering.
This material will be complemented with the use of software tools (e.g. MATLAB) for computation and a DSP (Digital Signal Processor) based development platform for the implementation of signal processing algorithms in the laboratory.
Objectives: On completing this subject the student should be able to:
  • Apply fundamental mathematical tools, in particular stochastic techniques, in the analysis and design of signal processing systems;
  • Recognise estimation problems and design, implement and analyses algorithms for solving them;
  • Use software packages such as MATLAB for the analysis and design of signal processing systems;
  • Implement signal processing systems with DSP based development platforms.

  • One written examination, not exceeding three hours at the end of semester, worth 70%;
  • Continuous assessment of submitted project work, not exceeding 30 pages over the semester, worth 30%.

Prescribed Texts: TBA
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:
  • Ability to apply knowledge of basic science and engineering fundamentals
  • In-depth technical competence in at least one engineering discipline
  • Ability to undertake problem identification, formulation and solution
  • Ability to utilise a systems approach to design and operational performance
  • Capacity for independent critical thought, rational inquiry and self-directed learning
  • Ability to communicate effectively, with the engineering team and with the community at large
Notes: Credit may not be obtained for both ELEN40004(431-461) Signal processing 2 and ELEN90052 Advanced Signal Processing
Related Course(s): Bachelor of Engineering (Biomedical)Biosignals
Bachelor of Engineering (Computer Engineering)
Bachelor of Engineering (Electrical Engineering)
Bachelor of Engineering (Electrical) and Bachelor of Arts
Bachelor of Engineering (Electrical) and Bachelor of Commerce
Bachelor of Engineering (EngineeringManagement) Electrical
Postgraduate Certificate in Engineering
Related Majors/Minors/Specialisations: Master of Engineering (Electrical)

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