Model-based Parameter Estimation
Model-Based Parameter Estimation is a methodological framework that employs a predefined mathematical or physical model to infer unknown system parameters from observed data by optimizing the fit between the model's predicted outputs and the measured sparse samples, while explicitly accounting for artifacts such as wellbore storage effects.
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Petre Stoica, Yngve Selén · IEEE Signal Processing Magazine · 2004 · 1.3K citations
Computing, Data Science, Algorithms +16
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Pennsylvania State University
State College, United States
15 h-index
33 publications
4K citations
University of Maryland, College Park
College Park, United States
11 h-index
21 publications
818 citations

Centre National de la Recherche Scientifique
Paris, France
11 h-index
26 publications
768 citations
University of California, Los Angeles
Los Angeles, United States
7 h-index
12 publications
1.1K citations

Delft University of Technology
Delft, The Netherlands
7 h-index
16 publications
612 citations
Stanford University
Stanford, United States
7 h-index
16 publications
1.8K citations
ETH Zurich
Zurich, Switzerland
7 h-index
15 publications
595 citations

KTH Royal Institute of Technology
Stockholm, Sweden
7 h-index
17 publications
587 citations
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