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Bayesian and Markov chain Monte Carlo methods for identifying nonlinear systems in the presence of uncertainty

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Figure

Figure 1. The embodiment of Ockham’s Razor in the marginal likelihood (original explanation described in [7]).
Figure 2. (a–c) Sampling from a two-dimensional distribution using the Metropolis algorithm.
Figure 3. MCMC becoming stuck in a ‘local trap’.
Figure 4. (a) Test rig and (b) schematic of rotational energy harvester at the University of Southampton Institute of Soundand Vibration.
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