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- W4313228701 abstract "Mathematical models for phenomena in the physical sciences are typically parameter-dependent, and the estimation of parameters that optimally model the trends suggested by experimental observation depends on how model-observation discrepancies are quantified. Commonly used parameter estimation techniques based on least-squares minimization of the model-observation discrepancies assume that the discrepancies are quantified with the L2-norm applied to a discrepancy function. While techniques based on such an assumption work well for many applications, other applications are better suited for least-squared minimization approaches that are based on other norm or inner-product induced topologies. Motivated by an application in the material sciences, the new alternative least-squares approach is defined and an insightful analytical comparison with a baseline least-squares approach is provided." @default.
- W4313228701 created "2023-01-06" @default.
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- W4313228701 date "2022-01-01" @default.
- W4313228701 modified "2023-10-18" @default.
- W4313228701 title "Mathematical Analysis of Two Approaches for Optimal Parameter Estimates to Modeling Time Dependent Properties of Viscoelastic Materials" @default.
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- W4313228701 doi "https://doi.org/10.4236/am.2022.1312059" @default.
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