Computer Science and Electronic Engineering (School of)
Undergraduate: Level 5
Thursday 03 October 2019
Saturday 14 December 2019
29 April 2019
Requisites for this module
BENGH610 Electronic Engineering,
BENGH611 Electronic Engineering (Including Year Abroad),
BENGH61P Electronic Engineering (Including Foundation Year),
BENGHP10 Electronic Engineering (Including Placement Year),
MENGH613 Electronic Engineering,
MENGH614 Electronic Engineering (Integrated Masters, Including Placement Year),
BENGH641 Communications Engineering,
BENGHP41 Communications Engineering (Including Foundation Year),
BENGHPK1 Communications Engineering (Including Placement Year),
BENGHQ41 Communications Engineering (Including Year Abroad),
MENGH642 Communications Engineering,
BENGH615 Robotic Engineering,
BENGH616 Robotic Engineering (Including Year Abroad),
BENGH617 Robotic Engineering (Including Placement Year),
BSC H631 Electronics,
BSC H632 Electronics (Including Year Abroad),
BSC H633 Electronics (Including Placement Year),
BENGH730 Mechatronic Systems,
BENGH731 Mechatronic Systems (Including Year Abroad),
BENGH732 Mechatronic Systems (Including Placement Year)
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.
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.
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.
. 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.
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.
Lectures, Labs and Classes
This module does not appear to have a published bibliography.
Assessment items, weightings and deadlines
|Coursework / exam
||Progress Test 1 - Wk 5
||Progress Test 2 - Wk 8
||Progress Test 3 - Wk 11
||Matlab laboratory (oral/logbook assessment) - Wk 11
||120 minutes during Summer (Main Period) (Main)
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
Dr Yunfei Chen
University of Warwick
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).
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