Digital signal processing
B Lithgow
4 points * 26 lecture hours, 26 laboratory hours * Second semester * Caulfield * Prerequisites: MAC2901
Objectives To obtain an understanding of the fundamental principles which form the basis of the 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 Non-recursive filter design, recursive filter design, adaptive filters, 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 of applications.
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
Strum R D and Kirk D E First principles of discrete systems and digital signal processing Addison-Wesley, 1988
Kak A C and Slaney M Principles of computerised tomographic imaging IEEE Press, 1988
| Published by Monash University, Clayton, Victoria
3168 Copyright © Monash University 1996 - All Rights Reserved - Caution Authorised by the Academic Registrar December 1996 |