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

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Balikhin M (2010) Data based quest for solar wind-magnetosphere coupling function COUPLING in Geophysical Research Letters

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

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Boynton R (2015) Online NARMAX model for electron fluxes at GEO in Annales Geophysicae

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Genes C (2019) Robust Recovery of Missing Data in Electricity Distribution Systems in IEEE Transactions on Smart Grid

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Guo L (2014) A Spatial Frequency Domain Analysis of the Belousov-Zhabotinsky Reaction in International Journal of Bifurcation and Chaos

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Guo Y (2013) A parametric frequency response method for non-linear time-varying systems in International Journal of Systems Science

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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) A SIMPLE SCALAR COUPLED MAP LATTICE MODEL FOR EXCITABLE MEDIA in International Journal of Bifurcation and Chaos

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Guo Y (2014) An iterative orthogonal forward regression algorithm in International Journal of Systems Science

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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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He F (2014) A nonlinear generalization of spectral Granger causality. in IEEE transactions on bio-medical engineering

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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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Li Y (2011) Identification of Time-Varying Systems Using Multi-Wavelet Basis Functions in IEEE Transactions on Control Systems Technology

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Sarrigiannis PG (2014) Quantitative EEG analysis using error reduction ratio-causality test; validation on simulated and real EEG data. in Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology

 
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