Displaying similar documents to “Nonlinear state prediction by separation approach for continuous-discrete stochastic systems”

Numerical analysis of nonlinear model of excited carrier decay

Natalija Tumanova, Raimondas Čiegis, Mečislavas Meilūnas (2013)

Open Mathematics

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This paper presents a mathematical model for photo-excited carrier decay in a semiconductor. Due to the carrier trapping states and recombination centers in the bandgap, the carrier decay process is defined by the system of nonlinear differential equations. The system of nonlinear ordinary differential equations is approximated by linearized backward Euler scheme. Some a priori estimates of the discrete solution are obtained and the convergence of the linearized backward Euler method...

A simple scheme for semi-recursive identification of Hammerstein system nonlinearity by Haar wavelets

Przemysław Śliwiński, Zygmunt Hasiewicz, Paweł Wachel (2013)

International Journal of Applied Mathematics and Computer Science

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A simple semi-recursive routine for nonlinearity recovery in Hammerstein systems is proposed. The identification scheme is based on the Haar wavelet kernel and possesses a simple and compact form. The convergence of the algorithm is established and the asymptotic rate of convergence (independent of the input density smoothness) is shown for piecewiseLipschitz nonlinearities. The numerical stability of the algorithm is verified. Simulation experiments for a small and moderate number of...

Preface

P. Chartier, L. Petzold (2009)

ESAIM: Mathematical Modelling and Numerical Analysis

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Nonparametric instrumental variables for identification of block-oriented systems

Grzegorz Mzyk (2013)

International Journal of Applied Mathematics and Computer Science

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A combined, parametric-nonparametric identification algorithm for a special case of NARMAX systems is proposed. The parameters of individual blocks are aggregated in one matrix (including mixed products of parameters). The matrix is estimated by an instrumental variables technique with the instruments generated by a nonparametric kernel method. Finally, the result is decomposed to obtain parameters of the system elements. The consistency of the proposed estimate is proved and the rate...