B Lithgow
4 points · 26 lecture hours and 26 project/laboratory/tutorial hours · Second semester · Clayton · Prerequisites: MAC2901
Objectives To obtain an understanding of the fundamental principles which form the basis of DSP and image processing systems; the assumptions used in the formulation of computer programs for implementation of DSP applications. To gain knowledge of DSP applications and specialist techniques used to optimally solve them; the criteria used in the design, simulation, construction and debugging of DSP hardware. An introduction to artificial intelligence.
Synopsis Applications using the TMS320 family processors, digital image processing, wavelets, a comparison of artificial intelligence systems: neural networks, expert systems, fuzzy logic. Computerised tomography will be used as an example image processing application.
Assessment Examination (3 hours): 60% · Practical work and laboratory work: 40%
Recommended texts
Gonzales R C and Woods R E Digital image processing
Addison-Wesley, 1992
Kak A C and Slaney M Principles of computerised tomographic imaging IEEE
Press, 1988
Strum R D and Kirk D E First principles of discrete systems and digital
signal processing Addison-Wesley, 1988