Signal Analysis for Computing - CO662

Location Term Level Credits (ECTS) Current Convenor 2019-20
Medway Autumn
View Timetable
6 15 (7.5)

Pre-requisites

None

Restrictions

None

2019-20

Overview

This module will provide the student with an understanding of basic principles of signals; introduce digitisation methods such as sampling, quantisation and coding; describe and apply signal analysis techniques, such as segmentation, noise reduction, filtering, spectral analysis, feature extraction and classification (including recognition and decision making) to solve practical signal analysis problems using Matlab.

Details

Contact hours

Total contact hours: 30
Private study hours: 120
Total study hours: 150

Method of assessment

1 piece of coursework (40 hours) (50%)
2 hour unseen exam (50%)

Indicative reading

R. Palaniappan, "Biological Signal Analysis," BookBoon, 2010, http://bookboon.com/en/textbooks/it-programming/introduction-to-biological-signal-analysis. The free to download ebook has the core material on signal analysis and classification.
I. McLoughlin, "Applied Speech and Audio Processing," Cambridge University Press, 2009
B. W. Schuller, “Intelligent Audio Analysis,” Springer, 2013
L. Sornmo and P. Laguna, “Bioelectrical Signal Processing in Cardiac and Neurological Applications,” Elsevier Academic Press, 2005
R.M. Rangayyan, “Biomedical Signal Analysis, 2nd ed.,” IEEE-Wiley Press, 2015
S. Mitra, “Digital Signal Processing: A Computer-based Approach, 4th ed.,” McGraw-Hill, 2010

See the library reading list for this module (Medway)

Learning outcomes

On successfully completing the module students will be able to:
Demonstrate a systematic understanding of basic principles of digital signals
Describe and comment upon the different categories of digital signals ?
Identify and apply pre- and post- processing techniques, such as conditioning, filtering, feature extraction, classification and hypothesis testing techniques for various types of signals
Demonstrate the ability to use Matlab for analysis and visualisation of digital signals
Apply their knowledge and understanding to initiate and carry out real world signal analysis problem solving
Make effective use of general computing facilities
Engage with research literature and other information sources
Communicate technical issues clearly in written formats
Manage their own learning and development, including time management and organisational skills

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