Identifiability limits in ultrasonic microstructure characterization are governed by forward-map structure and intrinsic stochastic variability, with combined observables improving conditioning through complementary sensitivities.
Autonomouscharacterizationofgrainsizedistributionusingnonlinearlambwaves based on deep learning.The Journal of the Acoustical Society of America, 152(3):1913–1921
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Identifiability Limits in Ultrasonic Microstructure Characterisation: A Canonical and Stochastic Framework
Identifiability limits in ultrasonic microstructure characterization are governed by forward-map structure and intrinsic stochastic variability, with combined observables improving conditioning through complementary sensitivities.