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1 Chowdhury, S. R., "Variance reduced particle filters for structural system identification problems" 2012
2 Hoshiya, M., "Structural identification by extended Kalman Filter" 110 (110): 1757-1770, 1984
3 Chang, S. Y., "State and parameter estimation with a sequential importance resampling(SIR)particle filter in a three dimensional groundwater pollutant transport model" 2012
4 Doucet, A., "Sequential Monte Carlo Methods in Practice" Springer 2001
5 Smyth, A. W., "On-line parametric identification of MDOF nonlinear hysteretic systems" 125 (125): 133-142, 1999
6 Gordon, N. J., "Novel approach to nonlinear/non-Gaussian Bayesian state estimation" 140 (140): 107-113, 1993
7 Namdeo, V., "Nonlinear structural dynamical system identification using adaptive particle filters" 306 (306): 524-563, 2007
8 Kitagawa, G., "Monte Carlo Filter and smoother for Non-Gaussian nonlinear state space model" 5 (5): 1-25, 1996
9 Yun, C. B., "Identification of nonlinear structural dynamics systems" 8 (8): 187-203, 1980
10 Yoshida, I., "Health monitoring algorithm by the Monte Carlo Filter based on non-Gaussian noise" 24 (24): 101-107, 2002
11 Higuchi, T., "Genetic algorithm and Monte Carlo Filter" 44 : 19-30, 1996
12 Samanta, B., "Engineering system fault detection using particle filters" 95-101, 2009
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15 Ching, J., "Bayesian state and parameter estimation of uncertain dynamical systems" 21 (21): 81-96, 2006
16 Sato, T., "Adaptive Monte Carlo Filter and structural identification" 2001
17 Sato, T., "Adaptive H infinite filter : Its application to structural identification" 124 (124): 1233-1240, 1998
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19 Loh, C. H., "A three-stage identification approach for hysteretic systems" 22 : 85-97, 1993
20 Simon, J. J., "A new extension of the Kalman Filter to nonlinear systems" SPIE 1997
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