- Code ENGN6537
- Unit Value 6 units
- Offered by Research School of Engineering
- ANU College ANU College of Engineering and Computer Science
- Course subject Engineering
- Areas of interest Engineering, Electronics
- Academic career PGRD
- Mode of delivery In Person
- Co-taught Course
First Semester 2017
See Future Offerings
Digital Signal Processing (DSP) has become over the years an important tool with applications in Electrical and Mechanical Engineering fields. DSP has penetrated many domains of applications, such as digital communications, medical imaging, audio & video systems, consumer electronics, robotics, remote sensing, finance etc. The Discrete-Time Signal Processing paradigm is a convenient setting to analyse the basic principles of DSP. At the end of this course, the students should be able to understand these basic principles, and apply fundamental algorithms and methods to analyse and design discrete-time systems for modern DSP applications. Though the course will focus on the study of theoretical concepts, methods and algorithms, the student will be confronted with application and implementation issues, through various examples and assignments requiring personal computer work including processing of real-world signals. ENGN 6537 Discrete Time Signal Processing builds directly on Signals & Systems Theory (ENGN2228 Signal Processing) by developing the students' understanding of the principles of advanced signal processing theory. Specific Topics include:
Review of signals & systems Theory (Discrete LTI systems, Convolution, Difference Equations).
Sampling of continuous time signals (basic principles, changing sampling rate, pre-filtering to avoid aliasing and quantization errors).
Transform Analysis of LTI systems (frequency response of LTI, all pass systems, minimum phase systems)
IIR & FIR filters and filter design techniques.
Discrete Time Fourier Transform (DFT) and FFT algorithms.
Fourier analysis of real signals with DFT.
Overview of microprocessor architectures for DSP, implementation aspects of modern DSP algorithms.
Upon successful completion, students will have the knowledge and skills to:On successfully completing this course, students will be able to:
- Analyse and evaluate the properties of LTI systems in terms of its z-transforms.
- Understand the sampling theorem and perform sampling on continuous-time signals by applying advanced knowledge of the sampling theory (i.e., aliasing, quantisation errors, pre-filtering).
- Apply the concepts of all-pass and minimum-phase systems to analyse the LTI system and address complex design problems.
- Evaluate design problems related to frequency selective processing and design FIR/IIR filters.
- Construct systems for spectral estimation of real signals by applying advanced knowledge of Fourier techniques.
- Judge implementation aspects of modern DSP algorithms.
- Apply the relevant theoretical knowledge to design and analyse a practical discrete-time signal system, such as a radar or audio system, using Matlab platform.
- Investigate advanced signal processing techniques and implement complicated systems based on the course material.
- Weekly Problems: 15%,
- Mid-term Quiz: 15%,
- Matlab project: 25 %,
- Final Exam: 45 %
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Requisite and Incompatibility
- A. V. Oppenheim & R. W. Schafer, Discrete-Time Signal Processing", New International Edition (3e), Pearson, 2013.
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- Unit value:
- 6 units
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Offerings, Dates and Class Summary Links
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Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|3221||20 Feb 2017||27 Feb 2017||31 Mar 2017||26 May 2017||In Person||N/A|