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    JI Keynote Lecture 2019

    时间: 2019-01-07 10:38:42  来源:   发布单位:   点击:

    JI Keynote Lecture 2019 <1>

    Speaker 1: Associate Professor, Qinghua Guo

    Seminar 1: Nonlinearity Modelling and Mitigation for LED Communications

    Place 1: Room 301, Science Hall  

    Time 1: 9:00-11:00 AM, Jan 9th, 2019

    Overview 1

       In recent years, light-emitting diodes (LEDs) technology, known as “Green Illumination”, is growing rapidly. The research on LED communications is attracting more and more attention. LED is the major source of nonlinearity in LED communications, and the nonlinearity needs to be modelled effectively and thereby mitigated through pre-distortion or post-distortion to avoid severe degradation of communication performance. In this talk, we will discuss several LED nonlinearity modelling and mitigation techniques and the relevant receivers which can efficiently mitigate LED nonlinearity and inter-symbol interference distortions in LED communications.

    Speakers Information:

       Dr Qinghua Guo received his PhD degree in electronic engineering from City University of Hong Kong in 2008. He is now an Associate Professor with the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Australia. His research interest includes communication signal processing, optoelectronic signal processing, etc. He has published more than 100 SCI journal papers and 40 conference papers in the related areas.

     

    JI Keynote Lecture 2019 <2>

    Speaker 1: Associate Professor, Qinghua Guo

    Seminar 2: Graphical Model-Based Learning and Inference for Communications and Instrumentation

    Place 2: Room 101, Graduate School

    Time 2: 14:30-16:30 PM, Jan 10th, 2019

    Overview 2

    Graphical models are an intuitive way of representing and visualizing the dependence structure of (large collections of) random variables with complex interactions. Graphical models allow us to define general message passing algorithms which run in the graphs to achieve efficient probabilistic inference and learning by exploiting the structure of the graph representations. In this talk, we will discuss the applications of graphical models and message passing algorithms to wireless communications and instrumentation to significantly improve system performance.

    Speakers Information:

       Dr Qinghua Guo received his PhD degree in electronic engineering from City University of Hong Kong in 2008. He is now an Associate Professor with the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Australia. His research interest includes communication signal processing, optoelectronic signal processing, etc. He has published more than 100 SCI journal papers and 40 conference papers in the related areas.

     

     

     


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