Signal Processing and Complex Systems Research Team

Images of some of the team's research

The Signal Processing and Complex Systems research team is a large multidisciplinary research team that carries out world-class research in nonlinear systems identification; information and signal processing including generalised or higher order frequency response functions, wavelets and fractals; cellular automata, spatio-temporal systems and brain imaging; nonlinear systems analysis and design including chaos; machine learning and neural networks; machine vision; synthetic biology, stem cell dynamics, medicine and related fields.

Examples of successfully conducted/on-going research undertaken by the team include: a unified theory for block structured nonlinear systems; derivation of the NARMAX [Nonlinear AutoRegressive Moving Average with eXogenous inputs] model and associated model structure detection and estimation procedures including the orthogonal least squares algorithm; a generic class of model validation procedures; a new theory for the analysis of nonlinear systems in the frequency domain including a new class of filters called energy transfer filters; the response spectrum map; a wavelet modelling framework; a new theoretical framework for sub-harmonic and severely nonlinear systems; the introduction of several new neural network training algorithms; formulation of a new class of nonlinear adaptive noise cancellation procedures; the derivation of new procedures for the analysis and identification of cellular automata, spatio-temporal systems, and brain image analysis; and the derivation of computer vision systems for autonomous guided vehicles. Many of these results are widely cited and have been taken up and applied in new domains by other researchers.

We have many contacts with industry both in the UK and internationally. Recent applications include studies relating to oil platforms in the north sea, steel strip mills, electric arc furnaces, chemical process plants, electric machine systems, shock absorbers, vibration suppression in car bodies, diesel engines, power generation plants, racing cars, space plasma turbulence, magnetosperic dynamics, crop growth, brain images, autonomous guided vehicles, river flow and catchment systems, pollutant modelling, macro-econometric modelling and forecasting, crystal growth, modelling for biology, systems and synthetic biology, Drosophila retinal networks, EEG, ECG, stem cells and many more.

The team is housed in a modern research laboratory and is supported by a network of Unix workstations and PC's. We operate an open flexible working environment and take great care to promote the strengths of all in a stimulating, happy and friendly atmosphere.

The team welcomes researchers of all nationalities for PhD studies and has a continual recruitment program for able PhD candidates and postdoctoral research fellows. The team can occasionally offer scholarships for well qualified students to support studies for a PhD.

Most Highly Cited

The contribution of our research team has recently been recognised by the Institute of Scientific Information [ISI], Web of Science, of the USA "in recognition of outstanding achievements and contributions to the international research community". The ISI have compiled a database of the worlds most highly cited researchers in various disciplines over the past fifty years. The contribution made by our research team, over this period, is recognised by an entry in the list of the most highly cited researchers in the category that covers all branches of engineering subjects. Based on the H-index, which measures the importance, significance and impact of a scientist's cumulative research contribution, S A Billings is ranked fourth in the UK and tenth in Europe for all engineering disciplnes. For more information, and to view the list of the world's most highly cited researchers, follow the link below:

The world's most highly cited researchers' website

Centre for Signal Processing in Neuroimaging and Systems Neuroscience

Members of the Signal Processing and Complex Systems research team are founding members of the Centre for Signal Processing in Neuroimaging and Systems Neuroscience (SPiNSN). This centre supports the joint research activities between the Departments of Psychology and Automatic Control and Systems Engineering in neuroimaging and systems neuroscience.

Centre for Signal Processing in Neuroimaging and Systems Neuroscience

Centre for Signal Processing and Complex Systems

The Centre for Signal Processing and Complex Systems develops system identification, signal processing, modelling, and analysis methods to address the challenging problems and highly complex behaviours in the life sciences, medicine, and other related fields.

Centre for Signal Processing and Complex Systems


Enquires should be directed to:

Professor S A Billings

Professor S A Billings
Director, Signal Processing and Complex Systems Team
Department of Automatic Control and Systems Engineering
The University of Sheffield
Mappin street
S1 3JD

Tel: 0114 222 5232
Fax: 0114 222 5661

email :