- UCAS course code
- HH36
- UCAS institution code
- M20
Bachelor of Engineering (BEng)
BEng Mechatronic Engineering
Explore the world of robotics and automation through the dynamic study of mechatronics.
- Typical A-level offer: AAA including specific subjects
- Typical contextual A-level offer: AAB including specific subjects
- Refugee/care-experienced offer: ABB including specific subjects
- Typical International Baccalaureate offer: 36 points overall with 6,6,6 at HL, including specific requirements
Fees and funding
Fees
Tuition fees for home students commencing their studies in September 2025 will be £9,535 per annum (subject to Parliamentary approval). Tuition fees for international students will be £34,000 per annum. For general information please see the undergraduate finance pages.
Policy on additional costs
All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).
Scholarships/sponsorships
For information about scholarships and bursaries please visit our undergraduate student finance pages and our Department funding pages .
Course unit details:
Digital Signal Processing
Unit code | EEEN30201 |
---|---|
Credit rating | 10 |
Unit level | Level 3 |
Teaching period(s) | Semester 2 |
Available as a free choice unit? | No |
Overview
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 design 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.
Pre/co-requisites
Unit title | Unit code | Requirement type | Description |
---|---|---|---|
Signals and Systems | EEEN20131 | Pre-Requisite | Compulsory |
Aims
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
Learning outcomes
On the successful completion of the course, students will be able to:
ILO 1 Demonstrate a mastery and detailed knowledge of the founding principles of DSP, and understand how the various fundamental equations both operate and are constructed.
ILO 2 Recognise the different classes of problem in digital signal processing, and to decide upon appropriate methodologies in their solution.
ILO 3 Code and test off-line and real-time DSP algorithms, both using PCs and dedicated DSP hardware.
ILO 4 Design, from system level, a complete DSP engineering solution (hardware and software specification) intended for real-time use.
ILO 5 Use an Eclipse-based development and debugging framework.
The above ILOs are developed and assessed.
Teaching and learning methods
Lectures; laboratories; interactive PDF notes that include fully developed software, clickable audio notes and audio examples.
Assessment methods
Method | Weight |
---|---|
Other | 20% |
Written exam | 80% |
Coursework (20% of total unit assessment):
Laboratory in real-time DSP. This comprises six programming tasks (team based) and one design report (individual)
Feedback methods
.
Recommended reading
Digital Signal Processing: A Practical Approach, Emmanuel C. Ifeachor and B Jervis
Foundations of Digital Signal Processing: Theory, algorithms and hardware design, Patrick Gaydecki
Study hours
Scheduled activity hours | |
---|---|
Lectures | 20 |
Practical classes & workshops | 9 |
Tutorials | 4 |
Independent study hours | |
---|---|
Independent study | 67 |
Teaching staff
Staff member | Role |
---|---|
Patrick Gaydecki | Unit coordinator |