Engineering Mathematics

The details
Computer Science and Electronic Engineering (School of)
Colchester Campus
Autumn Special
Undergraduate: Level 5
Thursday 03 October 2019
Saturday 14 December 2019
29 April 2019


Requisites for this module


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


This module does not appear to have a published bibliography.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Weighting
Coursework Progress Test 1 - Wk 5 17.5%
Coursework Progress Test 2 - Wk 8 17.5%
Coursework Progress Test 3 - Wk 11 15%
Coursework Matlab laboratory (oral/logbook assessment) - Wk 11 50%
Exam 120 minutes during Summer (Main Period) (Main)

Overall assessment

Coursework Exam
40% 60%


Coursework Exam
40% 60%
Module supervisor and teaching staff
Dr Manoj Thakur
CSEE School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770



External examiner

Dr Yunfei Chen
University of Warwick
Associate Professor
Available via Moodle
Of 45 hours, 22 (48.9%) 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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