Spatio-Temporal Systems Estimation, Modelling and Analysis
Lead Research Organisation:
University of Sheffield
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.
Organisations
Publications
Guo L
(2014)
Spatial frequency range analysis for the nonlinear Schrödinger equation
in Nonlinear Dynamics
Guo L
(2014)
A Spatial Frequency Domain Analysis of the Belousov-Zhabotinsky Reaction
in International Journal of Bifurcation and Chaos
Vidal-Rosas EE
(2014)
Reduced-order modeling of light transport in tissue for real-time monitoring of brain hemodynamics using diffuse optical tomography.
in Journal of biomedical optics
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
Yifan Zhao
(2013)
A Parametric Method to Measure Time-Varying Linear and Nonlinear Causality With Applications to EEG Data
in IEEE Transactions on Biomedical Engineering
Zhu Q
(2013)
Review of rational (total) nonlinear dynamic system modelling, identification, and control
in International Journal of Systems Science
Zhao Y
(2013)
A new NARX-based Granger linear and nonlinear casual influence detection method with applications to EEG data.
in Journal of neuroscience methods
He F
(2013)
Identification and frequency domain analysis of non-stationary and nonlinear systems using time-varying NARMAX models
in International Journal of Systems Science
Wang S
(2013)
Model term selection for spatio-temporal system identification using mutual information
in International Journal of Systems Science
| 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 |