Unit Title: Digital Signal Processing




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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

  5. The discrete Fourier transform (DFT) and its efficient computation (FFT)

  6. Digital filters


Unit Calendar

Study Area Week No

Introduction to DSP 1

Discrete-time signals 1-2

Discrete-time systems 3-4

The z-transform and the Fourier transforms 5-7

of discrete-time signals

The discrete Fourier transform (DFT) and 8-10

its efficient computation (FFT)

Digital filters 12

Revision 13

Examination 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

Tutorial examples sheet will be handed out at the end of formal teaching of this study area.


Discrete-Time SystemsIntroduction 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 z-transform 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.


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.

  2. Vinay K. Ingle, John G. Proakis, Digital Signal Processing using Matlab, Brooks/Cole, 2000 (Matlab will be used in the workshop assignment)

  3. Richard G. Lyons, Understanding Digital Signal Processing, Addison Wesley, 1997

  4. Trevor J. Terrell, Lik-Kwan Shark, Digital Signal Processing (A Student Guide), Macmillan Press Ltd, 1996

  5. Rodger E. Ziemer, William H. Tranter, D. Ronald, Signals & Systems (Continuous and Discrete), Prentice Hall, 1998

  6. Bernard Mulgrew, Peter Grant, John Thompson, Digital Signal Processing (Concepts & Applications), Macmillan Press Ltd, 1999

  7. 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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