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MEng Electronic Engineering with Industrial Experience / Course details
Year of entry: 2021
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Course unit details:
Digital Signal Processing
|Unit level||Level 3|
|Teaching period(s)||Semester 2|
|Offered by||Department of Electrical & Electronic Engineering|
|Available as a free choice unit?||No|
This unit will cover the following:
Introduction to DSP and linear systems.
Convolution and correlation. Using impulse function to represent discrete signals; description of convolution using linear superposition; Fourier interpretation of convolution; simple filtering using convolution; auto-correlation and cross-correlation; cross-correlation, matched filters and signal-to-noise ratio enhancement; temporal smearing and pseudo random bit sequences.
Fourier analysis. The continuous trigonometric Fourier series for periodic signals; data representation and graphing; the continuous trigonometric Fourier series for aperiodic signals; observations on the continuous Fourier series; exponential representation of the Fourier series; the continuous Fourier transform; discrete Fourier analysis; introduction to the fast Fourier transform.
Discrete Fourier properties and processing. Window functions; spectral leakage; representation of spectral data; considerations of phase; key properties of the discrete Fourier transform; discrete Fourier transform signal processing.
The Laplace transform. Its use in differential equation; the s-plane; circuit analysis; analogue filter design.
The z-transform and digital filter design. Definitions and properties; digital filters, diagrams and the z transfer function; filter deign using pole-zero placement; FIR and IIR filters: merits and disadvantages.
Signal sampling. The process of sampling; signal digitisation; principles of analogue to digital and digital to analogue conversion; ADCs and DACs in system.
Design of FIR filters. The window method; phase linearity; the frequency sampling method; software for arbitrary FIR design; inverse filtering and signal reconstruction.
Design of IIR filters. The bilinear z-transform; the BZT and 2nd order passive systems; digital Butterworth and Chebyshev IIR filters; pole-zero placement revisited; biquad algorithm design strategies; FIR expression of IIR responses.
Adaptive filters. Brief theory of adaptive FIR filters; the least mean square (LMS) adaptive FIR algorithm; use of the adaptive filter in system modelling; delayed (single) input adaptive LMS filters for noise removal; the true (dual input) adaptive LMS filter.
Real time DSP: the DSP563xx design. System architecture; assembly code programming; real time system design; peripheral interfacing; FIR, IIR and adaptive filters in real time.
DSP in audio applications: reverberation, equalization and string synthesis.
|Unit title||Unit code||Requirement type||Description|
|Signals and Systems||EEEN20027||Pre-Requisite||Compulsory|
This course unit detail provides the framework for delivery in 2020/21 and may be subject to change due to any additional Covid-19 impact. Please see Blackboard / course unit related emails for any further updates.
The course unit aims to:
- Provide a thorough and complete introduction to the subject of modern digital signal processing;
- Emphasise the links between the theoretical foundations of the subject and the essentially practical nature of its realisation;
- Encourage and understand through the use of algorithms and real world examples;
- Provide useful skills through detailed practical laboratories, which explore both off-line and real-time DSP software and hardware
On the successful completion of the course, students will be able to:
Demonstrate a mastery and detailed knowledge of the founding principles of DSP, and understand how the various fundamental equations both operate and are constructed.
Recognise the different classes of problem in digital signal processing, and to decide upon appropriate methodologies in their solution.
Code and test off-line and real-time DSP algorithms, both using PCs and dedicated DSP hardware.
Design, from system level, a complete DSP engineering solution (hardware and software specification) intended for real-time use.
Use an Eclipse-based development and debugging framework.
Teaching and learning methods
Lectures; laboratories; interactive PDF notes that include fully developed software, clickable audio notes and audio examples.
Coursework (20% of total unit assessment):
Laboratory in real-time DSP. This comprises six programming tasks (team based) and one design report (individual)
Digital Signal Processing: A Practical Approach, Emmanuel C. Ifeachor and B Jervis
Foundations of Digital Signal Processing: Theory, algorithms and hardware design, Patrick Gaydecki
|Scheduled activity hours|
|Practical classes & workshops||9|
|Independent study hours|
|Patrick Gaydecki||Unit coordinator|