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
Tonge PD
(2010)
Prepatterning in the stem cell compartment.
in PloS one
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
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
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
Friederich U
(2012)
Reverse Engineering Gain Adaptation in Sensory Systems
Zhu Q
(2013)
Review of rational (total) nonlinear dynamic system modelling, identification, and control
in International Journal of Systems Science
Genes C
(2019)
Robust Recovery of Missing Data in Electricity Distribution Systems
in IEEE Transactions on Smart Grid
Guo L
(2014)
Spatial frequency range analysis for the nonlinear Schrödinger equation
in Nonlinear Dynamics
ZHAO Y
(2011)
SPATIO-TEMPORAL MODELING OF WAVE FORMATION IN AN EXCITABLE CHEMICAL MEDIUM BASED ON A REVISED FITZHUGH-NAGUMO MODEL
in International Journal of Bifurcation and Chaos
He F
(2013)
Spectral analysis for nonstationary and nonlinear systems: a discrete-time-model-based approach.
in IEEE transactions on bio-medical engineering
Song Z
(2012)
Stochastic, adaptive sampling of information by microvilli in fly photoreceptors.
in Current biology : CB
Munir S
(2019)
Structuring an integrated air quality monitoring network in large urban areas - Discussing the purpose, criteria and deployment strategy
in Atmospheric Environment: X
Akanyeti, O
(2011)
Studying robot environment interaction via transparent controllers
Kadirkamanathan V
(2012)
The Neutrophil's Eye-View: Inference and Visualisation of the Chemoattractant Field Driving Cell Chemotaxis In Vivo
in PLoS ONE
Guo L
(2013)
The use of Volterra series in the analysis of the nonlinear Schrödinger equation
in Nonlinear Dynamics
Li Y
(2012)
Time-varying linear and nonlinear parametric model for Granger causality analysis.
in Physical review. E, Statistical, nonlinear, and soft matter physics
Li Y
(2011)
Time-varying model identification for time-frequency feature extraction from EEG data.
in Journal of neuroscience methods
Wei H
(2010)
Time-varying parametric modelling and time-dependent spectral characterisation with applications to EEG signals using multiwavelets
in International Journal of Modelling, Identification and Control
Balikhin M
(2011)
Using the NARMAX approach to model the evolution of energetic electrons fluxes at geostationary orbit NARMAX MODELLING OF RADIATION BELT ELECTRON FLUXES
in Geophysical Research Letters
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
Guo Y
(2013)
Volterra Series Approximation of a Class of Nonlinear Dynamical Systems Using the Adomian Decomposition Method
in Nonlinear Dynamics
Friederich, U
(2013)
We now know what fly photoreceptors compute
| 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 |