A particle filtering and kernel smoothing-based approach for new design component prognostics

A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking

M.S. Arulampalam, Simon Maskell, Neil Gordon et al. · IEEE Transactions on Signal Processing · 2002 · 11.5K citations

Computing, Physics, Bayesian Data Analysis +14

On sequential Monte Carlo sampling methods for Bayesian filtering

Arnaud Doucet, Simon Godsill, Christophe Andrieu · Statistics and Computing · 2000 · 4.4K citations

Natural Sciences, Computer Science, Mathematics +10

Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications

Jay Lee, Fangji Wu, Wenyu Zhao et al. · Mechanical Systems and Signal Processing · 2013 · 1.5K citations

Engineering, Operations Management, Maintenance Engineering +11

Prognostics of lithium-ion batteries based on Dempster–Shafer theory and the Bayesian Monte Carlo method

Wei He, Nicholas Williard, Michael Osterman et al. · Journal of Power Sources · 2011 · 1K citations

Computing, Computational Engineering, Bayesian Data Analysis +15

An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo

Olivier Cappé, Simon Godsill, Éric Moulines · Proceedings of the IEEE · 2007 · 1K citations

Computing, Computer Science, Computer Vision +15