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

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

Munir S
(2019)
Analysing the performance of low-cost air quality sensors, their drivers, relative benefits and calibration in cities-a case study in Sheffield
in Environmental Monitoring and Assessment

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

Tan L
(2018)
Ecological network analysis on intra-city metabolism of functional urban areas in England and Wales
in Resources, Conservation and Recycling

Billings S
(2015)
Identification of nonlinear systems with non-persistent excitation using an iterative forward orthogonal least squares regression Algorithm
in International Journal of Modelling, Identification and Control

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

Li Y
(2015)
Identification of nonlinear time-varying systems using an online sliding-window and common model structure selection (CMSS) approach with applications to EEG
in International Journal of Systems Science

Guo Y
(2015)
Identification of continuous-time models for nonlinear dynamic systems from discrete data
in International Journal of Systems Science

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

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