Spatio-Temporal Systems Estimation, Modelling and Analysis

Lead Research Organisation: University of Sheffield
Department Name: Automatic Control and Systems Eng

Abstract

Systems where the dynamics at any point depends upon the dynamics back in time and the dynamics at neighbouring spatial locations are ubiquitous. These space-time or spatio-temporal systems represent an enormous class of highly complex dynamical systems that have been largely ignored in studies to date. It is the spatial interactions over a neighbourhood of influence that together with the temporal dynamics combine to produce evolving patterns of complex interacting behaviours. Real life examples of spatio-temporal systems are easy to find and range from neuro-imaging applications to stem cells and reaction diffusion systems. The main objective of this research study will be to derive generic systems identification and parameter estimation based procedures to identify models of these complex systems, to develop model validation methods for this model class, to investigate characterisation based on invariant dynamic measures, and to apply the results to a range of both simulated and real spatio-temporal systems.

Publications

10 25 50

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Boynton R (2011) Data derived NARMAX Dst model in Annales Geophysicae

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GUO Y (2012) CHARACTERIZING NONLINEAR SPATIO-TEMPORAL SYSTEMS IN THE FREQUENCY DOMAIN in International Journal of Bifurcation and Chaos

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GUO Y (2012) IDENTIFICATION OF EXCITABLE MEDIA USING A SCALAR COUPLED MAP LATTICE MODEL in International Journal of Bifurcation and Chaos

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Y Zhao (Author) (2012) Identification of hybrid Cellular Automata using image segmentation methods in Journal of Cellular Automata

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Zhao Y (2012) Identification of radius-vector functions of interface evolution for star-shaped crystal growth in Mathematical and Computer Modelling of Dynamical Systems

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Li Y (2012) Time-varying linear and nonlinear parametric model for Granger causality analysis. in Physical review. E, Statistical, nonlinear, and soft matter physics

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Zhao Y (2012) A New Adaptive Fast Cellular Automaton Neighborhood Detection and Rule Identification Algorithm. in IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society

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Y Zhao (Author) (2012) Application of totalistic Cellular Automata for noise filtering in image processing in Journal of Cellular Automata

 
Description Developed new theories, methods and algorithms to analyze, model, simulate and control complex spatio-temporal systems
Exploitation Route Applications range from modelling crystal growth, to space weather forecasting and flow control
Sectors Agriculture

Food and Drink

Chemicals

Communities and Social Services/Policy

Environment

Healthcare

 
Description By medics in treating epilepsy and deep brain stimulation. Space weather forecasting models - Real time forecast of the >800 keV electron flux at geosynchronous orbit
First Year Of Impact 2015
Sector Chemicals,Environment,Healthcare,Pharmaceuticals and Medical Biotechnology
Impact Types Societal

 
Description Program Grant
Amount $900,000 (USD)
Funding ID RGP0001/2012 
Organisation Human Frontier Science Program (HFSP) 
Sector Charity/Non Profit
Country France
Start 05/2012 
End 06/2015