Displaying similar documents to “On two methods for the parameter estimation problem with spatio-temporal FRAP data”

On the optimization of initial conditions for a model parameter estimation

Matonoha, Ctirad, Papáček, Štěpán, Kindermann, Stefan

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The design of an experiment, e.g., the setting of initial conditions, strongly influences the accuracy of the process of determining model parameters from data. The key concept relies on the analysis of the sensitivity of the measured output with respect to the model parameters. Based on this approach we optimize an experimental design factor, the initial condition for an inverse problem of a model parameter estimation. Our approach, although case independent, is illustrated at the FRAP...

On estimation of diffusion coefficient based on spatio-temporal FRAP images: An inverse ill-posed problem

Kaňa, Radek, Matonoha, Ctirad, Papáček, Štěpán, Soukup, Jindřich

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We present the method for determination of phycobilisomes diffusivity (diffusion coefficient D ) on thylakoid membrane from fluorescence recovery after photobleaching (FRAP) experiments. This was usually done by analytical models consisting mainly of a simple curve fitting procedure. However, analytical models need some unrealistic conditions to be supposed. Our method, based on finite difference approximation of the process governed by the Fickian diffusion equation and on the minimization...

Distributed H ∞ estimation for moving target under switching multi-agent network

Hu Chen, Qin Weiwei, He Bing, Liu Gang (2015)

Kybernetika

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In this paper, the distributed H ∞ estimation problem is investigated for a moving target with local communication and switching topology. Based on the solution of the algebraic Riccati equation, a recursive algorithm is proposed using constant gain. The stability of the proposed algorithm is analysed by using the Lyapounov method, and a lower bound for estimation errors is obtained for the proposed common H ∞ filter. Moreover, a bound for the H ∞ parameter is obtained by means of the solution...

Estimation of the density of a determinantal process

Yannick Baraud (2013)

Confluentes Mathematici

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We consider the problem of estimating the density Π of a determinantal process N from the observation of n independent copies of it. We use an aggregation procedure based on robust testing to build our estimator. We establish non-asymptotic risk bounds with respect to the Hellinger loss and deduce, when n goes to infinity, uniform rates of convergence over classes of densities Π of interest.

On orthogonal series estimation of bounded regression functions

Waldemar Popiński (2001)

Applicationes Mathematicae

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The problem of nonparametric estimation of a bounded regression function f ∈ L ² ( [ a , b ] d ) , [a,b] ⊂ ℝ, d ≥ 1, using an orthonormal system of functions e k , k=1,2,..., is considered in the case when the observations follow the model Y i = f ( X i ) + η i , i=1,...,n, where X i and η i are i.i.d. copies of independent random variables X and η, respectively, the distribution of X has density ϱ, and η has mean zero and finite variance. The estimators are constructed by proper truncation of the function f ̂ ₙ ( x ) = ∑ k = 1 N ( n ) c ̂ k e k ( x ) , where the coefficients c ̂ ₁ , . . . , c ̂ N ( n ) ...

On cumulative 13 C breath tests: An effort to improve the accuracy of test results revealed a substantial uncertainty in input data

Chleboun, Jan, Kocna, Petr

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A cumulative 1 3 C breath test can be used to detect a pancreatic disorder, for example. The test is burdened by uncertain input data. Among them, the estimation of CO 2 production rate is a key issue. An established estimate based on the body surface area could be replaced by an estimate using the basal metabolic rate. Although the latter estimate might be considered more appropriate than the former, the differences between them are large in some sex and agegroups. Such disagreements pose...