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The eigenvalue approach using integral transforms has been employed and the transforms have been inverted by using a numerical technique.
Fourier transform has been employed and the transform has been inverted by using a numerical inversion technique.
The integral transforms have been inverted by using a numerical technique to obtain the displacement, microrotation and stress components in the physical domain.
The analytical expressions of displacement components, normal force stress, tangential force stress and temperature field so obtained have been inverted by using a numerical technique.
The integral transforms have been inverted by using a numerical technique to obtain the normal force stress, normal displacement, tangential force stress, tangential couple stress and volume fraction field in the physical domain for the two different sources.
The integral transforms have been inverted by using a numerical technique to obtain the normal force stress, normal displacement, tangential couple stress and volume fraction field in the physical domain for the two different sources.
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The synthetic dataset was inverted by using the same parameters as those for the second-step inversions including smoothing, 2.2 km/s of V FT, seven time windows with 0.45 s intervals, a smoothed ramp function of 0.9 s in duration, 27 s data length, the band-pass filtering of 0.05 1.0 Hz, and selected stations.
These equations are inverted by searching the RF solution space using simulated annealing global optimization technique.
The proposed probabilistic model is efficiently inverted by using the Variational Bayes framework under a convenient mean-field approximation (VB-GLM).
The synthetic data were then inverted by using the same inversion strategy as that performed for the actual data.
Then the more singular part is analytically inverted by using some special technique like the Riemann-Hilbert Problem (RHP) method [7, 9, 10].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com