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.
Organisations
Publications
Zheng Y
(2012)
Balanced excitation and inhibition: model based analysis of local field potentials.
in NeuroImage
Zheng Y
(2010)
A dynamic model of neurovascular coupling: implications for blood vessel dilation and constriction.
in NeuroImage
Wei HL
(2010)
An adaptive wavelet neural network for spatio-temporal system identification.
in Neural networks : the official journal of the International Neural Network Society
Zhao Y
(2012)
Identification of radius-vector functions of interface evolution for star-shaped crystal growth
in Mathematical and Computer Modelling of Dynamical Systems
Holmes GR
(2012)
Repelled from the wound, or randomly dispersed? Reverse migration behaviour of neutrophils characterized by dynamic modelling.
in Journal of the Royal Society, Interface
Li Y
(2011)
Time-varying model identification for time-frequency feature extraction from EEG data.
in Journal of neuroscience methods
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
Boynton R
(2011)
Using the NARMAX OLS-ERR algorithm to obtain the most influential coupling functions that affect the evolution of the magnetosphere DATA-DEDUCED COUPLING FUNCTIONS
in Journal of Geophysical Research: Space Physics
Y Zhao (Author)
(2012)
Identification of hybrid Cellular Automata using image segmentation methods
in Journal of Cellular Automata
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 |