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Green, PL and Worden, K (2015) Bayesian and Markov chain Monte Carlo methods for identifying nonlinear systems in the presence of uncertainty. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 373 (2051). 20140405-.

Green, PL (2015) Bayesian system identification of a nonlinear dynamical system using a novel variant of Simulated Annealing. Mechanical Systems and Signal Processing, 52-53 (Februa). pp. 133-146.

Green, PL, Cross, EJ and Worden, K (2015) Bayesian system identification of dynamical systems using highly informative training data. Mechanical Systems and Signal Processing, 56-57. pp. 109-122.

Green, PL (2015) Bayesian system identification of dynamical systems using large sets of training data: A MCMC solution. PROBABILISTIC ENGINEERING MECHANICS, 42. pp. 54-63.

Green, PL and Maskell, S ORCID: 0000-0003-1917-2913 (2017) Estimating the parameters of dynamical systems from Big Data using Sequential Monte Carlo samplers. Mechanical Systems and Signal Processing, 93. pp. 379-396.

Green, PL, Worden, K and Sims, ND (2013) On the identification and modelling of friction in a randomly excited energy harvester. Journal of Sound and Vibration, 332 (19). pp. 4696-4708.

Green, PL, Chodora, E and Atamturktur, S (2018) On the identification of model error through observations of time-varying parameters. In: ISMA-USD Conference 2018.

Green, PL and Maskell, S ORCID: 0000-0003-1917-2913 (2016) Parameter estimation from big data using a sequential monte carlo sampler. In: ISMA2016.

Scott, M, Green, PL, O’Driscoll, D, Worden, K and Sims, N (2016) Sensitivity analysis of an Advanced Gas-cooled Reactor control rod model. Nuclear Engineering and Design, 305. pp. 514-523.

Green, PL, Worden, K, Atallah, K and Sims, ND (2012) The benefits of Duffing-type nonlinearities and electrical optimisation of a mono-stable energy harvester under white Gaussian excitations. Journal of Sound and Vibration, 331 (20). pp. 4504-4517.