System Identification and Model Validation for Spatio-Temporal Dynamical Systems
Lead Research Organisation:
University of Sheffield
Department Name: Automatic Control and Systems Eng
Abstract
Spatio-temporal systems are systems that evolve over both space and time. Until recently the lack of tools for analysing spatio-temporal systems has not been a limitation since most experiments produced purely temporal information in the form of measurements at a specific location or site. But there are many important systems where space and time are essential for explaining the observed phenomena. The main objective of this research study will be to investigate the identification of models of spatio-temporal systems where the cell entries can be either continuous or binary variables and to study the validation and other properties of this important class of nonlinear systems.
Publications

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

Sarrigiannis P
(2015)
Direct Functional Connectivity between the Thalamus (Vim) and the Contralateral Motor Cortex: Just a Single Case Observation or a Common Pathway in the Human Brain?
in Brain Stimulation

Zhao Y
(2016)
Inferring the variation of climatic and glaciological contributions to West Greenland iceberg discharge in the twentieth century
in Cold Regions Science and Technology

Guo L
(2007)
State-Space Reconstruction and Spatio-Temporal Prediction of Lattice Dynamical Systems
in IEEE Transactions on Automatic Control

Wei HL
(2009)
Lattice dynamical wavelet neural networks implemented using particle swarm optimization for spatio-temporal system identification.
in IEEE transactions on neural networks

Pan Y
(2008)
Neighborhood detection for the identification of spatiotemporal systems.
in IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society

GUO Y
(2011)
IDENTIFICATION OF n-STATE SPATIO-TEMPORAL DYNAMICAL SYSTEMS USING A POLYNOMIAL MODEL
in International Journal of Bifurcation and Chaos

Zhao Y
(2009)
Cellular automata modelling of dendritic crystal growth based on Moore and von Neumann neighbourhoods
in International Journal of Modelling, Identification and Control

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

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