Signal Processing 2

This subject has the following teaching availabilities in 2010:

431-325 Stochastic Signals and Systems, 431-335 Signal Processing 1 (Fundamentals)

On completion of this subject students should have a good understanding of signal processing methods for parameter estimation, and signal estimation and be able to design, analyse and implement such algorithms.

Topics include: Motivation for parameter estimation and filtering with examples. Parameter estimation: least squares and its properties, recursive least squares and least mean squares, optimisation-based methods, maximum likihood methods. Spectral estimation: periodogram, Barlett method, Welch method and Blackman-Tukey method. Optimal filters for signal estimation: Wiener filter, Kalman filter and Hidden Markov Model filter. Examples illustrating the wide application area of signal processing algorithms.

Project: Design, implementation and testing of signal processing algorithms. Implementation and testing of real time signal processing algorithms on a DSP board.

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;
• Recognize estimation problems and design, implement and analyse algorithms for solving them;
• Use software packages such as MATLAB for the analysis and design of signal processing systems;
• Prototype signal processing systems with DSP based hardware.

• Formally supervised written examination 3 hours: 70% (end of semester);
• Project reports (not exceeding 20 pages each): 30% (two projects, one in the first half of the semester and one in the second half of the ­semester).

This subject is not available as a breadth subject.

• Ability to apply knowledge of basic science and engineering fundamentals

• Ability to communicate effectively, not only with engineers but also with the community at large

• 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

• Ability to function effectively as an individual and in multi-disciplinary and multi-cultural teams, with the capacity to be a leader or manager as well as an effective team member

• Understanding of the social, cultural, global and environmental responsibilities of the professional engineer, and the need for sustainable development

• Expectation of the need to undertake lifelong learning, capacity to do so

• Capacity for independent critical thought, rational inquiry and self-directed learning

• Intellectual curiosity and creativity, including understanding of the philosophical and methodological bases of research activity

• Openness to new ideas and unconventional critiques of received wisdom

• Profound respect for truth and intellectual integrity, and for the ethics of scholarship