[PDF] Top 20 Nonlinear reduced models for state and parameter estimation
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Nonlinear reduced models for state and parameter estimation
... State estimation aims at approximately reconstructing the solution u to a parametrized par- tial differential equation from m linear measurements, when the parameter vector y is ...on reduced ... Voir le document complet
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State and parameter estimation for a class of schistosomiasis models
... ) and its estimate ˆ s(t) (blue) as given by the observer ( 9 ) when the measurements y(t) are corrupted by ...epidemic models are usually not known. A perennial problem in epidemic models is the ... Voir le document complet
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Supervisory observer for parameter and state estimation of nonlinear systems using the DIRECT algorithm
... observer for parameter and state estimation of nonlinear systems using the DIRECT algorithm Michelle ...Khong and Dragan Neˇsi´c Abstract— A supervisory observer is a ... Voir le document complet
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Nonlinear reduced models for state and parameter estimation
... of Reduced Basis Methods [ 23 ], see also [ 15 ] for the more general framework discussed ...surrogates for }u´upyq} permitting frequent parameter queries at an online stage needed, in ... Voir le document complet
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Sequential Monte Carlo smoothing with application to parameter estimation in non-linear state space models
... 100. For the subsequent 100 iterations, the number of particles in- creases at a quadratic rate with a final value (for the 250th Monte Carlo EM iteration) equal to N = ...moderate for a Monte ... Voir le document complet
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Estimation of State Space Models and Stochastic Volatility
... JPR and KSC using simulated and real data. We found that SV models estimated by single-move or multi-move MCMC can deliver, period after period, posterior distributions of smoothed volatilities with ... Voir le document complet
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Detecting and Adapting to Parameter Changes for Reduced Models of Dynamic Data-driven Application Systems
... healthy and in favorable conditions, and can become more conservative as it ages and ...capability estimation, needed to provide the vehicle with the ability to dynamically and ... Voir le document complet
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PBDW method for state estimation: error analysis for noisy data and nonlinear formulation
... constraints for the background coefficients ˆ z ...] and {a n , b n } n are estimated based on the bk ...hyper- parameter ξ associated with the regularizer, (ii) the background dimension N , ... Voir le document complet
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Mode discernibility and bounded-error state estimation for nonlinear hybrid systems
... SME for truly nonlinear hybrid systems is a challenging issue that has attracted only few ...Benazera and Trav´ e-Massuy` es (2009), who addressed hybrid systems with discrete-time only ... Voir le document complet
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Robust filtering for joint state parameter estimation for distributed mechanical systems
... formulation and optimization of filtering procedures aiming at estimating both the state variables and the parameters of a dynamical system has been an active field of research for several ... Voir le document complet
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Parameter Estimation in Nonlinear Mixed Effect Models Using saemix, an R Implementation of the SAEM Algorithm
... Kuhn and Lavielle ( 2005 )) and practical applications ( Girard and Mentr´ e ( 2005 ); Panhard and Samson ( 2009 ); Comets, Lavenu, and Lavielle ( 2011 ...obtained for only 5% of ... Voir le document complet
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State and parameter estimation in 1-D hyperbolic PDEs based on an adjoint method
... words: State estimation, Parameter estimation, Hyperbolic system, Adjoint method, Inverse problem, Saint-Venant model, Lighthill-Whitham-Richards model 1 Introduction In nature and ... Voir le document complet
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Reduced-order models for nonlinear vibrations of fluid-filled circular cylindrical shells: Comparison of POD and asymptotic nonlinear normal modes methods
... in state space and furnishes the adapted basis for decomposing ...valid for small values of the modal ...results for large values of the amplitude of the external forcing; in fact, the ... Voir le document complet
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Autoregressive Functions Estimation in Nonlinear Bifurcating Autoregressive Models
... , for any initial probability measure µ(dx) on R for X ∅ such that µ (1 + | · |) 2 < ...f0 and f1, in order to obtain the rate |Tn| −β/(2β+1) ...(νfι) and an estimator of ...(4)) ... Voir le document complet
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Parameter estimation in conditionally Gaussian pairwise Markov switching models and unsupervised smoothing
... algorithm for the unsupervised estimation of parameters in a class of linear JMS called “conditionally Gaussian pairwise Markov switching models” (CGPMSMs), which extends the family of classic ... Voir le document complet
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Joint-state and parameters estimation using nudging and SEIK filters for HIV mechanistic models
... field and historically arose in the context of geophysics – ...oceanographics and weather forecasting ...uncertainties and also estimating uncertain quantities – as for example the model ... Voir le document complet
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Modelisation and estimation of heterogeneous variances in nonlinear mixed models
... Introduction Nonlinear mixed effects models (NLMM) are more and more frequently used for anal- ysis of longitudinal data and repeated measurements in pharmacokinetics, growth and ... Voir le document complet
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Bayesian conditional Monte Carlo Algorithm for nonlinear time-series state estimation
... algorithms and can be seen as a temporal, rather than spatial, RB-PF ...Markovian models, including HMC or ...discussed and evaluated in terms of variance reduction ...filtering, and showed ... Voir le document complet
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Coupling stochastic EM and Approximate Bayesian computation for parameter inference in state-space models
... plots for the ESS values and the number of distinct particles at the smallest value of the ABC threshold ...times. For example from Figure 5 we can see that when ( ¯ M , M ) = (200, 1000) the number ... Voir le document complet
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Maximum a Posteriori Parameter Estimation for Hidden Markov Models
... EM and MCEM appear often trapped in congurations where one state of the Markov chain is not visited; besides, they are highly sensitive to the initial value, as shown by the variances in Table ...states ... Voir le document complet
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