CE262-5-AT-CA:
Engineering Mathematics

The details
2024/25
Computer Science and Electronic Engineering (School of)
Colchester Campus & Apprenticeship Location
Autumn Special
Undergraduate: Level 5
Current
Thursday 03 October 2024
Friday 13 December 2024
15
21 July 2023

 

Requisites for this module
(none)
(none)
(none)
(none)

 

CE223, CE269

Key module for

BENGH610DA Electronic Engineering

Module description

The module develops key mathematical skills that can be applied throughout Engineering. Subjects include integral transform and probability theory, developed in the context of concrete engineering problems in signal processing, circuit theory, reliability, and communication networks. The module will be exemplified using MATLAB.

Module aims

The module aims to introduce a number of concepts including: the spectrum of a signal; Fourier and Laplace transforms; simple probabilities; statistics and a variety of distributions.

Module learning outcomes

After completing this module, students will be expected to be able to:

1. Describe the concept of the spectrum of a signal
2. Find Fourier and Laplace transforms of simple time functions.
3. Find inverse Laplace transforms using partial fractions.
4. Calculate probabilities and conditional probabilities in simple examples.
5. Evaluate statistics such as mean and variance for a distribution.
6. Use a variety of distributions (uniform, binomial, Poisson, geometric, exponential, Gaussian) to model random phenomena.

Module information

Outline Syllabus

. Integral transforms:
The complex exponential form for Fourier series.
Fourier and Laplace transforms, and their application to simple waveforms. Properties: (linearity, scaling, time-shift, frequency shift, derivatives and integrals).

Application to first and second order circuits and systems.
Poles and zeros. Inverse transforms. Integral methods and partial fractions. Effects of feedback. Visualisation with Matlab.


. Probability:
Outcomes, sample spaces and events. Relative frequencies and probabilities. Conditional probabilites and independence.
Random variables, mean and variance.
Discrete distributions: uniform, binomial Poisson and geometric.
Continuous distributions: exponential and Gaussian.
The concept of a stochastic process. Reliability.
Simulation with Matlab.

Learning and teaching methods

Lectures, Labs and Classes

Bibliography

This module does not appear to have a published bibliography for this year.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Lab Test 1     30% 
Coursework   Lab Test 2     30% 
Coursework   Assignment 1    40% 
Exam  Main exam: In-Person, Open Book (Restricted), 120 minutes during Summer (Main Period) 
Exam  Reassessment Main exam: In-Person, Open Book (Restricted), 120 minutes during September (Reassessment Period) 

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
50% 50%

Reassessment

Coursework Exam
50% 50%
Module supervisor and teaching staff
Dr Sangeet Saha, email: sangeet.saha@essex.ac.uk.
Dr Sangeet Saha
School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770(non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770

 

Availability
No
No
No

External examiner

No external examiner information available for this module.
Resources
Available via Moodle
Of 49 hours, 26 (53.1%) hours available to students:
23 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).

 

Further information

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