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Dr Karin Ennser is an Associate Professor in the Department of Engineering
Dr Karin Ennser is an Associate Professor in the Department of Engineering
This module is devoted to the technology underlying optical fibre communication systems. It covers the fundamental properties of optical fibres and key components, and the principles of operation of systems including WDM based high capacity transport networks. The network architecture designs and performance metrics are examined. Modern topics are introduced such as advanced modulation formats, coherent communications, spectrum efficiency and Shannon limit capacity.
This module provides an introduction to several AI algorithms for engineering/physics problems. The specific engineering problems chosen to demonstrate the benefits offered by AI algorithms are 1) interpretation/processing of data from distributed sensors; 2) optimisation of material/device properties through physics informed neural network. The module teaches students basic statistical skills underpinning machine learning/artificial intelligence such as probability analysis and regression, as well as several case studies that use existing AI software to analyse engineering problems. Two assessments (exam and individual project, each carries 50%) for each term, designed to examine understanding of the basic machine leaning concepts and using the software to solve engineering problems, take place in the middle of term and end of term. Emphasis is placed on the use of existing software for tackling engineering problems.
To develop further methods of representing and analyzing signals and dynamic systems, to extend these concepts to sampled-data systems, to introduce concepts in digital signal processing and to use computer-aided methods for modelling and analysis.