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the time of going to press but may be subject to change. For the most
up-to-date information click on the Timetable button at the bottom of this page.
Optimum
and Adaptive Filtering 448 (620.448)
Outcomes: Students gain in-depth technical competence in analysis,
design and implementation of algorithms for optimum and adaptive filterings;
develop skills in the identification, formulation and solution of problems;
learn how to apply adaptive filters in control and communications engineering;
and understand innovations and advances in signal processing for modern control
and communications engineering.
Content: This unit provides a brief review of stochastic
processes: stationary processes and models, spectrum analysis; linear
optimum filtering: Weiner and Kalman filters and linear prediction; linear
adaptive filtering: method of steepest descent, stochastic gradient-based
algorithm; method of least squares, standard recursive least-squares
estimation, implementation techniques, finite precision and other effects;
application to control and communication systems.
Assessment: This comprises an examination,
class tests and worked laboratory assignments. The examination assesses
students’ understanding of adaptive systems theory and its application to
control and signal processing engineering practice. Class tests are used for
continuous assessment and enable students to monitor their own progress during
the semester. The laboratory assignments allow students to analyse, experiment
and evaluate the different algorithms and design implementations covered in
class, and explore the design and implementation of adaptive filters in control
and communications.
Web
page: http://swww.ee.uwa.edu.au/~oaf448/
Contact
hours: 60 (lectures: 36 hrs; tutorials/labs: 24
hrs)
Prerequisites: Signals and Systems 228 and Mathematics 218
Assumed
prior knowledge: analog and digital filter
design from Signals and Systems 328 or
equivalent and stochastic signal processing from Mathematics
358 or equivalent
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