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BEng Electrical and Electronic Engineering / Course details

Year of entry: 2021

Course unit details:
Digital Signal Processing

Unit code EEEN30029
Credit rating 10
Unit level Level 3
Teaching period(s) Semester 2
Offered by Department of Electrical & Electronic Engineering
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 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.

 

Pre/co-requisites

Unit title Unit code Requirement type Description
Signals and Systems EEEN20027 Pre-Requisite Compulsory

Aims

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

Learning outcomes

On the successful completion of the course, students will be able to:

Developed

Assessed

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.

Y

Y

ILO 2

Recognise the different classes of problem in digital signal processing, and to decide upon appropriate methodologies in their solution.

Y

Y

ILO 3

Code and test off-line and real-time DSP algorithms, both using PCs and dedicated DSP hardware.

Y

Y

ILO 4

Design, from system level, a complete DSP engineering solution (hardware and software specification) intended for real-time use.

Y

Y

ILO 5

Use an Eclipse-based development and debugging framework.

Y

Y

 

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)

 

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

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