Parameter estimation for mechanical systems via an explicit representation of uncertainty

Engineering Computations (Swansea, Wales)

Volumn 26, Issue 5, 2009, Pages 541-569

  Blanchard, Emmanuel ^a   Sandu, Adrian ^a   Sandu, Corina ^a  

^a State University   (United States)

Author keywords

Algorithmic languages; Bayesian statistical decision theory; Estimation; Mechanical systems; Polynomials; Systems theory

Indexed keywords

A-POSTERIORI PROBABILITIES; APRIORI; BAYESIAN COST FUNCTION; BAYESIAN ESTIMATIONS; BAYESIAN FRAMEWORKS; BAYESIAN STATISTICAL DECISION THEORY; BAYESIAN THEOREM; COMPUTATIONAL APPROACH; EXCITATION SIGNALS; EXPLICIT REPRESENTATION; GALERKIN APPROACH; MAXIMUM LIKELIHOOD ESTIMATE; MECHANICAL SYSTEMS; MONTE CARLO; NEW APPROACHES; NOISE LEVELS; NON-GAUSSIAN; NON-LINEAR DYNAMICS; PARAMETER UNCERTAINTY; PARAMETRIC UNCERTAINTIES; POLYNOMIAL CHAOS; POLYNOMIAL CHAOS THEORY; REGULARIZATION TECHNIQUE; STOCHASTIC COLLOCATION; SYSTEM DYNAMICS; SYSTEMS THEORY; TIME RESPONSE; UNCERTAIN PARAMETERS; UNDER-SAMPLING;

ALGORITHMIC LANGUAGES; BAYESIAN NETWORKS; COST BENEFIT ANALYSIS; COST FUNCTIONS; DECISION MAKING; DECISION THEORY; GAME THEORY; LINGUISTICS; MAXIMUM LIKELIHOOD ESTIMATION; MECHANICS; MECHATRONICS; OPERATIONS RESEARCH; PARAMETER ESTIMATION; POLYNOMIALS; PROBABILITY DENSITY FUNCTION; STATISTICS; SYSTEM THEORY; UNCERTAINTY ANALYSIS;

CHAOTIC SYSTEMS;

EID: 70149118361     PISSN: 02644401     EISSN: None     Source Type: Journal    
DOI: 10.1108/02644400910970185     Document Type: Article

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