Unit Title: Digital Signal Processing
Reference Number ECI-3-832
Level
3
Credits
1
Study hours
150 hrs, 36 hrs Lecture/Tutorials, 12 hrs Workshop, 102 hrs Student
Managed study.
Pre-requisites
Signals and Systems
School
Engineering
Division
Telecommunication and Internet Engineering
Co-ordinator
Dr Zhanfang ZHAO
(Room T409) tel: 020 7815 6340 email: zhaoza@lsbu.ac.uk
Aims
To introduce the basic principles of digital signal processing (DSP) and provide an
understanding of the fundamentals, implementation and applications of DSP
techniques.
Learning Outcomes
Upon successful completion of the unit, students will be able to:




Describe the nature and benefits of DSP.
Identify applications and typical uses of DSP.
Compare digital signal processing to analogue signal processing.
Understand and apply the basic concepts of DSP such as convolution, correlation,
sampling, z-transform, DFT and FFT.
 Define basic techniques for digital filtering.

Program basic signal processing tasks with MATLAB.
Unit Structure
The unit consists following topics:
1. Introduction to DSP
2. Discrete-time signals
3. Discrete-time systems
4. The z-transform and the Fourier transforms of discrete-time signals
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Unit Title: Digital Signal Processing
5. The discrete Fourier transform (DFT) and its efficient computation (FFT)
6. Digital filters
Unit Calendar
Study Area
Introduction to DSP
Discrete-time signals
Discrete-time systems
The z-transform and the Fourier transforms
of discrete-time signals
The discrete Fourier transform (DFT) and
its efficient computation (FFT)
Digital filters
Revision
Examination
Week No
1
1-2
3-4
5-7
8-10
12
13
14-15
Expansion of study areas:
Introduction to DSP – Overview of the basic definitions, advantages and applications of
DSP.
Learning outcome
You will be expected to know: the nature, the characteristic features, benefits and main
application fields of DSP.
Tutorial examples
Tutorial examples sheet will be handed out at the end of formal teaching of this study area.
Discrete-Time Signals – Basic concepts and operations concerning signals from a DSP
viewpoint.
Learning outcome
You will be expected to know: the classification of signals varying from analogue to digital,
the classification based on energy and power, sampling of analogue signals, definition of
discrete-time signal (DTS), convolution and correlation.
Tutorial examples
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Unit Title: Digital Signal Processing
Tutorial examples sheet will be handed out at the end of formal teaching of this study area.
Discrete-Time Systems – Introduction to discrete-time systems.
Learning outcome
You will be expected: to understand the basics concepts of discrete-time systems, system
properties like linearity, time-invariance, causality and stability, and linear time-invariant
(LTI) systems.
Tutorial examples
Tutorial examples sheet will be handed out at the end of formal teaching of this study area.
The Z-Transform and The Fourier Transforms of Discrete-Time Signals – Discuss the ztransform and the Fourier transforms (CTFT, DTFT).
Learning outcome
You will be expected: to understand the principles and properties of the z-transform and the
Fourier transforms, inversion of the z-transform, and the relation between different Fourier
transforms.
Tutorial examples
Tutorial examples sheet will be handed out at the end of formal teaching of this study area.
The Discrete Fourier Transform (DFT) and Its Efficient Computation (FFT) – The
details of DFT and FFT algorithm, power density spectrum and energy density spectrum of
signals.
Learning outcome
You will be expected: to be familiar with DFT and FFT algorithm; to know how get the
power density spectrum and energy density spectrum of signals.
Tutorial examples
Tutorial examples sheet will be handed out at the end of formal teaching of this study area.
Digital Filters – Designs of two main types of digital filters: the FIR (nonrecursive) and
IIR (recursive); computational process like lowpass filtering, bandpass filtering, interpolation,
integration, the generation of derivatives, etc.
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Unit Title: Digital Signal Processing
Learning outcome
You will be expected to understand the basic concepts involved in digital filtering and tackle
simple design problems.
Tutorial examples
Tutorial examples sheet will be handed out at the end of formal teaching of this study area.
Teaching and Learning Methods
Teaching will consist of 2 hour lecture each week, there will be 2 hour tutorial on odd weeks,
and 2 hour of laboratory work on even weeks. Lectures will cover all the main aspects of the
subject matter in the unit. Printed material, which will include some lecture material and
tutorial examples will be provided. In laboratory experiments, Matlab exercises will be set to
help the student gain experience with DSP algorithm implementation and applications.
Lectures and laboratory experiments are treated as a unified body of work. In addition, you
are required to carry out 102 hours of self managed study.
Assessment
There will be one 3-hour written examination (75%), and 1 workshop assignment (25%).
Each student is expected to maintain a log book on all the lab works. The log books will be
examined periodically during the lab sessions. Each student will be required to produce 1
formal written report on the workshop assignment. You will be required to submit the reports
and logbooks (will be specified in the early part of the semester) by the final submission date,
which will be notified during the semester allowing you sufficient time to complete your
work. You MUST submit your assignment, following the standard school procedure, to J200
between 10:00 and 16:00. Late submission will be penalized in accordance with the
University regulation.
Core Book List
1. Alan V. Oppenheim, Ronald W. Schafer, Discrete-Time Signal Processing, Prentice Hall,
1999
2. Hayes H. Digital Signal Processing, McGraw Hill, 1999
Background Reading
1. Buck John R. etc. Computer Explorations in Signals and Systems, Prentice Hall 2002.
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Unit Title: Digital Signal Processing
2. Vinay K. Ingle, John G. Proakis, Digital Signal Processing using Matlab, Brooks/Cole, 2000
3.
4.
5.
6.
7.
(Matlab will be used in the workshop assignment)
Richard G. Lyons, Understanding Digital Signal Processing, Addison Wesley, 1997
Trevor J. Terrell, Lik-Kwan Shark, Digital Signal Processing (A Student Guide), Macmillan
Press Ltd, 1996
Rodger E. Ziemer, William H. Tranter, D. Ronald, Signals & Systems (Continuous and
Discrete), Prentice Hall, 1998
Bernard Mulgrew, Peter Grant, John Thompson, Digital Signal Processing (Concepts &
Applications), Macmillan Press Ltd, 1999
Alan V. Oppenheim, Digital Signal Processing, Video Course Manual, MIT, 1975 (cassettes
are available in the library)
8. Proakis J. G., Manolakis D. G., Introduction to Digital Signal Processing, Macmillan Press
Ltd, 1988
9. Strum R. D., Kirk D. E., First Principles of Discrete System and digital signal Processing,
Addison Wesley, 1988
10.Todd K. Moon, Wynn C. Stirling, Mathematical Methods and Algorithms for Signal
Processing, Prentice Hall, 2000
11.Proakis J. G., Advanced digital Processing, Macmillan Press Ltd, 1992
12. Matlab Online Help: http://www.mathworks.com/
Study Hours
You may notice that this guide states that the unit requires 150 study hours, whereas
previous guides have defined each unit as 120 study hours. The University has made this
change in line with the way study time is likely to be expressed, in future, in the majority of
Universities. There is no change in teaching time, and no change in what you are expected to
do or achieve. The change concerns the way study time is measured. Previously, the unit was
defined as 120 hours work over 12 teaching weeks. The new measure is still 10 hours per
week over 15 weeks, including assessment.
The workload for a full time student is still expected to be approximately 40 hours per week.
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