Displaying similar documents to “Performance analysis of least squares algorithm for multivariable stochastic systems”

Asymptotic normality of randomly truncated stochastic algorithms

Jérôme Lelong (2013)

ESAIM: Probability and Statistics

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We study the convergence rate of randomly truncated stochastic algorithms, which consist in the truncation of the standard Robbins–Monro procedure on an increasing sequence of compact sets. Such a truncation is often required in practice to ensure convergence when standard algorithms fail because the expected-value function grows too fast. In this work, we give a self contained proof of a central limit theorem for this algorithm under local assumptions on the expected-value function,...

Identification of parameters in initial value problems for ordinary differential equations

Chleboun, Jan, Mikeš, Karel

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Scalar parameter values as well as initial condition values are to be identified in initial value problems for ordinary differential equations (ODE). To achieve this goal, computer algebra tools are combined with numerical tools in the MATLAB environment. The best fit is obtained through the minimization of the summed squares of the difference between measured data and ODE solution. The minimization is based on a gradient algorithm where the gradient of the summed squares is calculated...

Kriging and masurement errors

István Fazekas, Alexander G. Kukush (2005)

Discussiones Mathematicae Probability and Statistics

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A linear geostatistical model is considered. Properties of a universal kriging are studied when the locations of observations aremeasured with errors. Alternative prediction procedures are introduced and their least squares errors are analyzed.

Measuring and maintaining consistency: a hybrid FTF algorithm

James Bunch, Richard Le Borne, Ian Proudler (2001)

International Journal of Applied Mathematics and Computer Science

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Due to the versatility as well as its ease of implementation, the Fast Transversal Filters algorithm is attractive for many adaptive filtering applications. However, it is not widely used because of its undesirable tendency to diverge when operating in finite precision arithmetic. To compensate, modifications to the algorithm have been introduced that are either occasional (performed when a predefined condition(s) is violated) or structured as part of the normal update iteration. However,...