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https://doi.org/10.1007/978-981-19-0221-5points, but rather averaged values related to some not fully certain weight functions. The third reason is that, actually, the operator of the inverse remote sensing problem does not maintain some constant magnitudes in spatial and temporal coordinates, but, really, it is subjected by disturbances oHACK 发表于 2025-3-22 01:50:17
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Data Assimilation: Aims and Basic Concepts,accurate forecasts of future dynamical behaviour can be determined. Complete information defining all of the states of the system at a specified time are, however, rarely available. Moreover, both the models and the measured data contain inaccuracies and random noise. In this case, observations of t使成核 发表于 2025-3-22 19:05:30
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Fundamental Control Functions and Error Analysis,y (.) to the Hilbert space ., . ∈ ., . is a nonlinear operator mapping . into .. Let . = ..(0, ., .), ‖ · ‖. = (·,·)., . ∈ .. Let us introduce the functional . where α = const ≥ 0, .. ∈ ., .. are prescribed functions (observational data), .. is a Hilbert space (observational space), . : . → .. a linheterogeneous 发表于 2025-3-23 07:51:10
, Validation of Assimilation Algorithms, the chapter .. (which will hereafter be referred to as Part I). We recall eq. (4.1) of that chapter, which links the data vector ., belonging to data space ., with dimension ., to the state vector . to be determined, belonging to state space ., with dimension .