ISVR6045 Digital Signals and Systems
Knowledge and understanding
Having successfully completed the module, you will be able to demonstrate knowledge and understanding of:
- The theory and uses of the z-transform.
- A range of digital filter design methods.
- High resolution spectral analysis methods.
- The concept of non stationary and time frequency analysis.
Cognitive (thinking) skills
Having successfully completed the module, you will be able to:
- Read, understand and interpret the literature relating to a broader range of DSP techniques.
- Better appreciate the breadth of DSP algorithms available.
Practical, subject specific skills
Having successfully completed the module, you will be able to:
- To be able to predict the performance of a digital system and understand how modifications are likely to affect their performance.
- To use digital filter design tools, appreciating the limitations of the methods used.
- To be able to implement and appropriately use non-parametric spectral estimations.
Key transferable skills
Having successfully completed the module, you will be able to:
- Comprehend the power and limitations of DSP so that you appreciate where it can be used to enhance system performance.
Module Details
Title: Digital Signals and Systems
Code: ISVR6045
Year: MSc Sound and Vibration Studies
Semester: Semester 1
CATS points: 10 CAT points (= 100 hours) ECTS 5 ECTS points: NaN
Level: PostGradute taught
Co-ordinator(s): , Professor Paul White
Pre-requisites and / or co-requisites
None
The aims of this module are to:
- Provide the rationale and conceptual bases of some advanced signal processing topics.
- To introduce the student to the analytical and computational methods required for advanced analysis.
- To relate the analysis to applications and interpretation of the results.
- To ensure the student is equipped to understand and use current literature on advanced digital signal processing (DSP).
Digital Systems
- Auto-regressive (AR) modelling (through population models)
- Moving average (MA) systems
- ARMA processes
The Z-Transform
- Definition
- Representing the z-plane
- Poles and zeros
- Regions of convergence
- Inversion using, power series, partial fractions and contour integration
FIR Filter Design
- General filter design issues
- The windowing design method
- Frequency sampling
IIR Filter Design
- General comments on how to map analogue to digital systems
- Analogue filter designs
- Method of mapping differentials
- Impulse variance
- Bilinear transforms
High Resolution Spectral Estimation
- Time series models and the contrast between parametric and non-parametric estimation
- Auto-regressive moving-average models and parameter estimation
- Auto-regressive models and the Yule-Walker equations; maximum entropy methods; model order determination
- Capon's method
- Eigen-based methods; the MUSIC algorithm
Study time allocation
Contact hours: 24 hours lectures (2 h/wk); laboratory classes (2) up to 8 hours
Private study hours: 36 hours minimum, up to 76 hours
Total study time:
NaN
hours
Teaching and learning methods
2 lectures/week and two 2-hour laboratory classes.
Examples are provided to students in order to practice their analytical skills and these are backed up with interactive tutorial/laboratory sessions. Students are encouraged to read supporting texts and a booklist is provided.
Resources and reading list
Secondary text
Digital Signal Processing, 1975, A V Oppenheim
R W Schafer, 0132146355
Prentice-Hall: Englewood Cliffs, N J
Theory and Application of Digital Signal Processing,1975, L R Rabiner
B Gold, Prentice Hall
013914014
Modern Spectral Estimation, 1987, S M Kay, Prentice Hall
013598582X
Signals and Systems
1st Edition, 1983
2nd Edition, 1996, A V Oppenheim
A S Willsky
S Hamid Nawab, Prentice Hall
0138097313
136511759
Assessment methods
| Assessment method | Number | % contribution to final mark |
| Written exam | 1 | 80 |
| Assessed Laboratories | 2 | 20 |