Stochastic system identification via particle and sigma-point Kalman filtering

Scientia Iranica

Volumn 19, Issue 4, 2012, Pages 982-991

  Eftekhar Azam, S ^a   Bagherinia, M ^a   Mariani, S ^a  

^a POLITECNICO DI MILANO   (Italy)

Author keywords

Nonlinear constitutive laws; Particle filtering; Sigma point Kalman filtering; System identification

Indexed keywords

FAILURE (MECHANICAL); FRACTURE MECHANICS; IDENTIFICATION (CONTROL SYSTEMS); MONTE CARLO METHODS; RELIGIOUS BUILDINGS; STOCHASTIC SYSTEMS;

JOINT IDENTIFICATIONS; KALMAN-FILTERING; NON-LINEAR CONSTITUTIVE LAWS; PARTICLE FILTERING; SEVERE NONLINEARITY; SIGMA POINT KALMAN FILTER; STEADY-STATE MODELING; STRUCTURAL FAILURE;

KALMAN FILTERS;

ACCURACY ASSESSMENT; CALIBRATION; CONVERGENCE; FILTER; KALMAN FILTER; NONLINEARITY; PARTICLE SIZE; SOFTENING; STABILITY ANALYSIS; STEADY-STATE EQUILIBRIUM; STOCHASTICITY; STRUCTURAL ANALYSIS;

EID: 84865262559     PISSN: 10263098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.scient.2012.06.007     Document Type: Article

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