ELEC442 Digital Signal Processing

NOT OFFERED IN 2020

Paper Description

THIS PAPER WILL NOT BE OFFERED IN 2020

Introduces techniques of digital signal processing for deterministic signals. Covers discrete-time and linear time-invariant systems, difference equation description, the Z-transform, and advanced applications such as FIR filter design.

Students gain a working knowledge of discrete-time signals and systems, using a formalism that is natural to those systems. The paper covers discrete-time, linear time-invariant systems, the impulse response and system function, the frequency response, the Nyquist-Shannon sampling theorem, BIBO stability, difference equation description, the Z-transform and its connection to the discrete Fourier transform, and advanced applications.

Prerequisites:
None

This paper consists of 15 lectures and 6 tutorials. There are 3 assignments.

Assesment:
Final Exam 70%, Assignments 30%

Important information about assessment for ELEC442

Course Coordinator:
Associate Professor Colin Fox

After completing this paper students are expected to have achieved the following major learning objectives:

• Understand the consequences of the sampling theorem.
• Convert between continuous-time and discrete-time signals by using sampling theorem.
• Classify discrete-time signals and linear time-invariant systems using difference equations description.
• Apply the Z–transform to discrete-time signals and systems .
• Perform simple manipulations on Z-transforms, in particular find solutions to some simple systems given by their difference equations or their block diagrams.
• Determine the stability of a linear time-invariant system based on its poles and zeros structure.
• Design elementary infinite impulse response (IIR) and finite impulse response (FIR) filters.
• Construct Matlab functions, using the built-in DSP toolbox, corresponding to FIR filter specifications.

• An overall goal is to provide each student with confidence in their ability to describe linear time-invariant systems and discrete-time signals over the time-domain and over the frequency domain.
• Confidence in interpreting block diagram representation of a linear time-invariant system.

Topics:

• Classification of signals/systems
• Sampled waveforms
• Common waveforms
• Sampling theorem
• Signal reconstruction, Quantisation
• Introductions of the Z-transform
• Consequences of the sampling theorem
• Properties of the Z-transform
• Introduction of the system function
• Analysis of a linear time-invariant system over the z domain
• Manipulating the Z-transforms
• Block-diagram representation of linear time-invariant systems
• Causality and stability
• Introduction of digital filters and the two big classes: IIR and FIR filters
• Interpretation of a typical filter specification
• Four classes of linear phase digital filters
• Filter design by windowing technique

Formal University Information

The following information is from the University’s corporate web site.

Details

An introduction to techniques of digital signal processing for deterministic signals: discrete-time and linear time-invariant systems, difference equation description, the Z-transform, and advanced applications such as FIR filter design.

Paper title Digital Signal Processing ELEC442 Electronics 0.0833 10 points Not offered in 2022 (On campus) \$685.39 Tuition Fees for international students are elsewhere on this website.
Limited to
BSc(Hons), PGDipSci, MSc, MAppSc
Contact
colin.fox@otago.ac.nz
Teaching staff

Course co-ordinator: Associate Professor Colin Fox
Dr Tim Molteno

Textbooks
Textbooks are not required for this paper.
Global perspective, Interdisciplinary perspective, Lifelong learning, Scholarship, Communication, Critical thinking, Information literacy, Research, Self-motivation, Teamwork.
Learning Outcomes
By the end of the module students are expected to be able to:
1. Understand the consequences of the sampling theorem
2. Convert between continuous-time and discrete-time signals by using sampling theorem
3. Classify discrete-time signals and linear time-invariant systems using difference equations description
4. Apply the Z-transform to discrete-time signals and systems
5. Perform simple manipulations on Z-transforms, in particular find solutions to some simple systems given by their difference equations or their block diagrams
6. Determine the stability of a linear time-invariant system based on its poles and zeros structure
7. Design elementary infinite impulse response (IIR) and finite impulse response (FIR) filters
8. Construct Matlab functions using the built-in DSP toolbox corresponding to FIR filter specifications

Timetable

Not offered in 2022

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
None