[PDF] Top 20 Parameter estimation of models with many damped complex exponentials

... Figures 4.1 to 4.7 show th e Fourier transform and the spectrum obtained from the HSVD p aram eter estim ates for a variety of sim ulated d a ta sets. Figures 4.1 to 4.6 correspond to the d a ta sets used in C hapter 3 ... See full document

... RDE models in which there was one random variable ...variable parameter or a random variable parameter with a 2-parameter Weibull ...variable parameter, depending on the random choice ... See full document

... and parameter estimation to estimate an aggregate load’s ...motor models with different param- eters, and a ZIP ...additional models, and apply the approach to real data collected from a ... See full document

... The parameter estimation task is considered as an optimization problem, in which optimal model parameters are repeatedly determined by the difference between the model outputs and the corresponding ... See full document

... FAO 56 recommends Penman-Monteith equation. The method for calculating evapotranspiration from meteorological data requires various climatological and physical parameters. Some of the data are measured directly in ... See full document

... of parameter to be identified (e.g., 5 to 6) but yields models having limited accuracy for general operating ...the parameter estimation problem but yields a linear parameterization as ... See full document

... SRGM parameter estimation technique, but it can't do the same with other ...cases. Models that are good in general are not always the best choice for a particular dataset, and it is not possible to ... See full document

... In this paper we develop a framework for parameter estimation in macroscopic pedestrian models using individual trajectories – microscopic data. We consider a unidirectional flow of pedestrians in a ... See full document

... The paper concentrates on capability of genetic algorithms for parameter estimation of non-linear eco- nomic models. In the paper we test the ability of genetic algorithms to estimate of parameters ... See full document

... as many- core architectures geared to throttle embarrassingly parallel and computationally heavy graph- ics ...programming models such as CUDA and OpenCL has exposed enough of the hardware that allows the ... See full document

... mathematical models proposed by researchers at both the cellular level and the population level in the last decade (for example, see [1, 7, 16, 20, 22, 23, 24, 28, 29]) that attempt to understand the pathogenesis ... See full document

... The methods F OL, Laplae, Importane Sampling approximation, and Adaptive. Gaussian Quadrature give exat results when the model funtion f is linear in b[r] ... See full document

... The time varying mean and variance of the resulting RDE system (4.1) were estimated using stochastic collocation in which a sparse grid Gauss-Hermite quadrature rule was used. The mean concentration as well as the ... See full document

... Abstract. We present in this paper some results concerning the least sqaures estimation of parameters in a groundwater ow model. As is typically the case in eld studies, the form of the data is pointwise ... See full document

... Salt Lake City, UT). The pneumatic device was regulated via an air supply machine that allowed adjustments of hemodynamic parameter values and waveforms. The external ar- terial diameter was measured using ... See full document

... It is important to note the Levenberg Marquardt process in the PEST optimizer only reduces the error of the POD reduced model after each full ADH solve. PEST is unaware of how each iteration’s error compares to the ... See full document

... Smart materials, such as PZT, exhibit environment-dependent behavior which, under dynamic operating conditions, can require that model parameters be re-estimated to maintain the accuracy of the model and control ... See full document

... space during the process of param eter estimation with similar noise reduc­ tion characteristics. Both methodologies produce similar estimates of model param eters and system states, one should be able to discern ... See full document

... risk parameter in conditional volatility models. The risk parameter can be interpreted as a summary of conditional ...of estimation can be ... See full document

... and parameter values of a gene regulatory net- work model [25] that has become a benchmark in the ...The parameter values of metabolites X 1 , X 2 , X 4 , and X 5 were found correctly, but the parameters ... See full document