Results 241 to 250 of about 547,161 (285)

Nonlinear model reduction for large-scale structures via dual substructuring. [PDF]

Sci Rep
Flores PA.
europepmc   +1 more source

Improved Semiclassical Quantization of Bound States. [PDF]

J Phys Chem Lett
Pollak E.
europepmc   +1 more source

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Incomplete series expansion for function approximation

Structural and Multidisciplinary Optimization, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Albert A Groenwold, L F P Etman, J A Snyman   +2 more
exaly   +4 more sources

UNIFORM DIOPHANTINE APPROXIMATION TO CANTOR SERIES EXPANSION

Fractals, 2021
In this paper, we study the uniform Diophantine approximation in the nonautonomous dynamic system generated by the Cantor series expansions, which is formulated by considering the following set: [Formula: see text] It is of Hausdorff dimension [Formula: see text] for [Formula: see text] and is countable for [Formula: see text] under the condition that
YAN HAN, CHAO MA
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On the approximation by truncated sampling series expansions

Signal Processing, 1984
Abstract In this note we point out in which way the approximation of not necessarily bandlimited functions by sampling series is injured by additional truncation. We will also show how the rate of convergence is influenced by the features of the underlying kernel function.
S.E. Ries, V.W. Splettstößer
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Justifiability of the ZDO approximation in terms of a power series expansion

Theoretica Chimica Acta, 1970
The Zero Differential Overlap Approximation cannot be justified for all-valence-electron calculations in terms of a power series expansion of the overlap matrix, because the expansion diverges.
N. A. B. Gray, A. J. Stone
exaly   +2 more sources

MMD-ARMA approximation to the Volterra series expansion

Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284), 2002
Nonlinear filtering based on the Volterra series expansion is a powerful universal tool in signal processing. Due to the problem of increased complexity for higher orders and filter lengths, approximations up to third order nonlinearities using linear FIR-filters and multipliers have been developed earlier called multimemory decomposition (MMD). In our
V.S. Kafka, U. Appel
openaire   +1 more source