Searched for: subject:"Least%5C-squares%5C+approximation"
(1 - 5 of 5)
document
Wobbes, E. D. (author), Möller, M. (author), Galavi, V. (author), Vuik, Cornelis (author)
The material point method (MPM) is an effective computational tool for simulating problems involving large deformations. However, its direct mapping of the material-point data to the background grid frequently leads to severe inaccuracies. The standard function reconstruction techniques can considerably decrease these errors, but do not...
conference paper 2020
document
Klees, R. (author), Slobbe, D.C. (author), Farahani, H. (author)
The paper is about a methodology to combine a noisy satellite-only global gravity field model (GGM) with other noisy datasets to estimate a local quasi-geoid model using weighted least-squares techniques. In this way, we attempt to improve the quality of the estimated quasi-geoid model and to complement it with a full noise covariance matrix...
journal article 2018
document
Mahdad, A. (author), Doulgeris, P. (author), Blacquiere, G. (author)
Seismic acquisition is a trade-off between economy and quality. In conventional acquisition the time intervals between successive records are large enough to avoid interference in time. To obtain an efficient survey, the spatial source sampling is therefore often (too) large. However, in blending, or simultaneous acquisition, temporal overlap...
journal article 2011
document
Herrmann, F.J. (author), Wang, D. (author), Verschuur, D.J. (author)
In many exploration areas, successful separation of primaries and multiples greatly determines the quality of seismic imaging. Despite major advances made by surface-related multiple elimination (SRME), amplitude errors in the predicted multiples remain a problem. When these errors vary for each type of multiple in different ways (as a function...
journal article 2008
document
Zeng, L.J. (author), Ma, C. (author), Yang, H.X. (author), Xiao, R.J. (author), Li, J.Q. (author), Jansen, J. (author)
journal article 2008
Searched for: subject:"Least%5C-squares%5C+approximation"
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