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.
Total contact hours: 30
Private study hours: 120
Total study hours: 150
13.1 Main assessment methods
1 piece of coursework (40 hours) (50%)
2 hour unseen exam (50%)
13.2 Reassessment methods
Like for like.
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)
8. The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
8.1 Demonstrate a systematic understanding of basic principles of digital signals
8.2 Describe and comment upon the different categories of digital signals ?
8.3 Identify and apply pre- and post- processing techniques, such as conditioning, filtering, feature extraction, classification and hypothesis testing techniques for various types of signals
8.4 Demonstrate the ability to use Matlab for analysis and visualisation of digital signals
8.5 Apply their knowledge and understanding to initiate and carry out real world signal analysis problem solving
9. The intended generic learning outcomes.
On successfully completing the module students will be able to:
9.1 Make effective use of general computing facilities
9.2 Engage with research literature and other information sources
9.3 Communicate technical issues clearly in written formats
9.4 Manage their own learning and development, including time management and organisational skills
University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.