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RISFull Waveform Inversion on Jackdaw Ocean Bottom Nodes Data in North Sea
A FWI workflow for Jackdaw Ocean Bottom Node (OBN) dataset is described. Small receiver coverage, large receiver crossline spacing and no well information make it challengeable to apply FWI against this dataset. Improved ...
The double barrier inverse first passage problem for Wiener process with random starting point
A comparative study on sensitivity analysis of frequency and time domain full waveform inversion
The aim of this paper is to compare time domain and frequency domain full waveform inversion (FWI). We compare these inversions against random coherent and incoherent noises with different signal to noise ratios, source wavelet inaccuracy...
Reducing nonuniqueness in finite source inversion using rotational ground motions
Random doubly stochastic matrices: The circular law
Eliminating bias due to censoring in Kendall’s tau estimators for quasi independence of truncation and failure
Control of Interface Acceleration during Solidification Processes Using Inverse Heat Transfer Methods
In this paper, a computational method is established for acceleration control of phase
interface motion during solidification of pure materials. Inverse heat transfer methods are
applied to estimate the required time-dependent boundary...
Inverse boundary problem for estimating the boundary conditions of a radiant enclosure using the measurement of temperature on a solid object within the enclosure
In this paper, we present an inverse analysis to estimate the
thermal boundary conditions over a two-dimensional radiant
enclosure from the knowledge of the measured temperatures for
some points on a solid object within...
The asymptotic efficiencies of the MLE based on bivariate record values from bivariate normal distribution
One of the most important bivariate distributions in statistical inference is the bivariate
normal distribution. In this paper we consider ML estimation of parameters of bivariate
normal distribution using ...
ON THE SOLUTIONS OF OPERATOR EQUATIONS BXA = B = AXB VIA ∗-ORDER
the inverse of A along B. After that, under some mild conditions we prove that an operator X is a solution of BXA = B = AXB if and only if B ∗≤ AXA, where the ∗-order C ∗≤ D means CC∗ = DC∗, C∗C = C∗D. Moreover we present the general solution of the above...