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Search results for: error reports
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Scientific Reports
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Pharmacological Reports
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Error analysis for European IGS stations
PublicationEach of the GPS time series that describes the changes of topocentric components consists of a deterministic and a stochastic part, whose character influences the errors of the deterministic parameters. As to the uncertainties of reliable velocities of permanent satellite station systems, surveys that estimate and take into account any dependencies that may affect subsequent operational efficiency are very important. For this analysis,...
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The asymptotic formula for the error in orthogonal projection
PublicationW pracy podano formułę asymptotyczną błędu aproksymacji dla rzutów ortogonalnych w normie L^p.
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Asymptotic formulas for the error in linear interpolation
PublicationWyznaczono asymptotyczny wzór dla błędu w liniowej interpolacji z dowolnymi węzłami.
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Asymptotic error expansions for Schoenberg type operators
PublicationPrzedstawiono L^p błąd dla rozwinięć dla operatorów Schoenberga
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Asymptotic error expansions for Schoenberg type operators.
PublicationW pracy wyprowadzono rozwinięcie asymptotyczne dla błędu w L2 operatorówSchoenberga.
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An Approximation of the Zero Error Capacity by a Greedy Algorithm
PublicationWe present a greedy algorithm that determines a lower bound on the zero error capacity. The algorithm has many new advantages, e.g., it does not store a whole product graph in a computer memory and it uses the so-called distributions in all dimensions to get a better approximation of the zero error capacity. We also show an additional application of our algorithm.
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An Approximation of the Zero Error Capacity by a Greedy Algorithm.
PublicationWe present a greedy algorithm that determines a lower bound on the zero error capacity. The algorithm has many new advantages, e.g., it does not store a whole product graph in a computer memory and it uses the so-called distributions in all dimensions to get a better approximation of the zero error capacity. We also show an additional application of our algorithm.
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Akaike's final prediction error criterion revisited
PublicationWhen local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...