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# Introduction to Signal Processing with MATLAB - ELE00154M

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• Department: Electronic Engineering
• Module co-ordinator: Dr. Yury Zakharov
• Credit value: 20 credits
• Credit level: M
• Academic year of delivery: 2023-24

## Module summary

To introduce the students to the fundamental concepts of signal processing useful for the design and analysis of communication systems and MATLAB programming of signal processing techniques.

## Related modules

Pre-requisites:  Mathematics at a BEng level; Basics of Programming

## Module will run

Occurrence Teaching period
A Semester 1 2023-24

## Module aims

The module will introduce the students to the fundamental concepts of signal processing such as analogue and digital signals and systems, Fourier series, sampling, statistical signal processing and parameter estimation. The students will develop skills in design of signal processing techniques for communication systems. After successful completion of this module, students will also be able to write MATLAB functions and scripts to solve engineering problems, particularly related to signal processing for communications. This will allow them to conduct original research into communications engineering theory and practice as well as extract and critically evaluate data from complex communication systems through analytical and computational methods and modelling.

## Module learning outcomes

• Describe the signal sampling and reconstruction.

• Analyse continuous and discrete-time signals and systems in the time and frequency domain.

• Explain concepts of autocorrelation, convolution and linear systems.

• Describe statistical properties of signals.

• Explain principles of parameter estimation in noise.

• Undertake arithmetic on scalars, vectors and matrices

• Create 2D and 3D plots of mathematical functions and data

• Carry out Monte-Carlo simulations

• Solve a number of signal processing problems

## Module content

The students learn the fundamental concepts of signal processing, such as analogue and digital signals and systems, Fourier series, sampling, statistical signal processing and parameter estimation in a series of lectures and workshops. In these lectures and workshops, MATLAB examples are used to illustrate signal processing techniques. The fundamental concepts of signal processing are assessed in a closed-book examination. In practicals, starting from basic MATLAB functions for simple data processing, they move rapidly on, through a series of laboratory exercises, to data plotting, complex numbers, linear algebra and statistics. Students are encouraged in these laboratories to experiment and to learn about a range of built-in functions that MATLAB has to offer. They also get useful experience in programming techniques and in creating their own MATLAB functions. Finally, for their individual assignment, they write MATLAB code to analyse and synthesise signals for a real communication system.

## Assessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Introduction to Signal Processing with MATLAB Exam
2 hours 50
Essay/coursework
Individual Assignment
N/A 50

### Special assessment rules

None

There are 2 parts to the assessment:

Matlab coding exercise (MPR) - worth 50% of the module mark.

The assessment is based on completion of one of the exercises in the laboratory procedure document. Students are required to submit all their code and results for this exercise in the form of a report.

Closed-book Examination (YZ) - worth 50% of the module mark.

The assessment is based on the material delivered in the lectures and workshops.

### Reassessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Introduction to Signal Processing with MATLAB Reassessment Exam
2 hours 50
Essay/coursework
Individual Assignement Reassessment
N/A 50

## Module feedback

'Feedback’ at a university level can be understood as any part of the learning process which is designed to guide your progress through your degree programme. We aim to help you reflect on your own learning and help you feel more clear about your progress through clarifying what is expected of you in both formative and summative assessments. A comprehensive guide to feedback and to forms of feedback is available in the Guide to Assessment Standards, Marking and Feedback.

The School of PET aims to provide some form of feedback on all formative and summative assessments that are carried out during the degree programme. In general, feedback on any written work/assignments undertaken will be sufficient so as to indicate the nature of the changes needed in order to improve the work. The School will endeavour to return all exam feedback within the timescale set out in the University's Policy on Assessment Feedback Turnaround Time. The School would normally expect to adhere to the times given, however, it is possible that exceptional circumstances may delay feedback. The School will endeavour to keep such delays to a minimum. Please note that any marks released are subject to ratification by the Board of Examiners and Senate. Meetings at the start/end of each term provide you with an opportunity to discuss and reflect with your supervisor on your overall performance to date.

Statement of Feedback

Formative Feedback

• Problem sheets will be provided and marked in tutorial workshops, and you will have the opportunity to discuss your progress with the course tutor.

• Regular lab sessions will provide the opportunity to ask questions and receive verbal help and feedback about your progress in developing practical skills.

• Questions can be asked at any time during the in-class sessions or be Email, and will be answered as soon as possible.

Summative Feedback

Individual feedback will be provided on your written assessment.

Lathi, B. P. Signal Processing & Linear Systems, 2003, Oxford University Press, ISBN 0195219171.

Kay, S.M., Fundamentals of Statistical Signal processing: Estimation Theory, Prentice Hall, 1993

David McMahon - MATLAB Demystified - Prentice Hall

Vinay K. Ingle and John G. Proakis - Digital Signal Processing Using MATLAB - Cengage- Engineering; 2 edition (August 10, 2006)

Andr © Quinquis Digital Signal Processing Using Matlab (Hardcover) -Wiley-ISTE; 1 edition (April 4, 2008)

The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.