R. Murray-Smith

Neural networks for modelling and control of a non-linear dynamic system

R. Murray-Smith, D. Neumerkel, D. Sbarbaro-Hofer, 1992, Proceedings of the 1992 IEEE International Symposium on Intelligent Control.

Nonlinear modeling of FES-supported standing-up in paraplegia for selection of feedback sensors

T. Bajd, R. Murray-Smith, R. Kamnik, 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

On Fast Multi-Shot COVID-19 Interventions for Post Lock-Down Mitigation

E. Crisostomi, R. Shorten, R. Murray-Smith, 2020 .

Predictive control with Gaussian process models

J. Kocijan, R. Murray-Smith, C.E. Rasmussen, 2003, The IEEE Region 8 EUROCON 2003. Computer as a Tool..

Post-lockdown abatement of COVID-19 by fast periodic switching

E. Crisostomi, R. Shorten, R. Murray-Smith, 2020, PLoS Comput. Biol..

Nonparametric Identification of Linearizations and Uncertainty using Gaussian Process Models – Application to Robust Wheel Slip Control

R. Murray-Smith, T.A. Johansen, J. Hansen, 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

Modelling dynamic processes with clustered time-delay neurons

R. Murray-Smith, D. Neumerkel, H. Gollee, 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).