主讲人：Michael Small教授

主持人：邹  勇  副教授

开始时间：2013-03-05 14:00

讲座地址：闵行校区物理楼116报告厅

主办单位：物理系和科技处

报告人简介：

Michael Small is an Australian Research Council Future Fellow and Winthrop  Professor of Applied Mathematics in the School of Mathematics and Statistics at  The University of Western Australia (UWA). His research interests are complex  systems, nonlinear dynamics and chaos, and nonlinear time series analysis. Prof.  Small's work focusses on the application of mathematical methods to a variety of  problems in the real world: social and technological networks, neurodynamics,  modelling of physical systems, biomedical signal processing and financial  markets are a few examples. He is interested in how the structure of a complex  network affects the dynamical behaviour of its components and is developing  techniques to characterise and quantify regularity and atypical features in  complex networks. He is currently working on applications of complex networks  and dynamical complex networks to problems in systems biology, collective animal  motion and disease transmission.
Prior to joining UWA in 2012, Prof. Small  was with the Department of Electronic and Information Engineering at The Hong  Kong Polytechnic University. He is a Senior member of the IEEE and the  Australian Mathematics Society, and on the editorial board of several  international journals - including the International Journal of Bifurcations and  Chaos.  Prof. Small has published well over 130 journal articles and authored or  co-authored four books.

报告内容简介：

Complex System1s are everywhere - where-ever there is a large number of  interacting parts where the behaviour of the entire system is governed by the  manner of the interactions. Computers on the Internet, neurone in the human  brain, social interactions between people, and the biochemical processes within  a single cell are all examples.  However, complex systems may also arise in more  abstract settings - either from a time series recording of a dynamical system  (where the complex system consists of distinct states of the chaotic system), or  from sequences of notes in a musical composition. In this talk I will describe  several such situations and show how the methods of complex systems research can  be applied to extract useful information from such systems.