Digital signal processing
H Wu
4 points
* First semester
* Clayton
* Prerequisites:
RDT2220
Objectives At the completion of the subject students should be able to apply DSP techniques to signal processing tasks; design and implement algorithms to run on given DSP hardware; and continue their study in more advanced and specialised DSP topics as mentioned, but not limited to, the above.
Synopsis This subject, a continuation of DGS2220, addresses fundamental concepts, theory and techniques of digital signal processing (DSP); applications of digital signal processing and their implementations; and an appreciation of specific computer architectures used in digital signal processors. It provides the basis for more advanced topics in the area, such as advanced DSP, neural networks, video coding and compression, and advanced image and voice processing. The syllabus covers sampling of continuous-time signals and sampling rate conversion, digital signal processing systems, structures for discrete-time systems, digital filter design techniques, discrete Fourier transform (DFT) and computation of DFTs, discrete Hilbert transform and its applications, quantisation effect in digital signal processing; Fourier analysis of signals using the DFT, multirate digital signal processing, applications of digital signal processing, and DSP implementation using, for example, the TMS320C25/C30 digital signal processor(s).
Assessment Written examination (3 hours): 60%
* Laboratory practical
work: 40%
Recommended texts
Bateman A and Yates W Digital processing design Pitman, 1988
Ifeachor E C and Jervis B W Digital signal processing: A practical approach Addison-Wesley, 1993
Oppenheim A V and Schafer R W Discrete-time signal processing Prentice-Hall, 1989
| Published by Monash University, Clayton, Victoria
3168 Copyright © Monash University 1996 - All Rights Reserved - Caution Authorised by the Academic Registrar December 1996 |