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10 we further compare the convergence behaviour of the hybrid schemes for a set of eight test cases (including cases I and II). Here we plot the number of inner-loop iterations required for each outer-loop step in the Occam scheme for the Lanczos bi-diagonalization with explicit orthogonalization, and for the modified multitransmitter scheme. Nascido numa família humilde estudou no imposto em aposta esportiva Seminário de Diamantina, onde concluiu o curso de humanidades. The lines give the averages (over test cases) for each of the outer-loop iterations. The greatest increase in efficiency for the modified approach occurs on the first iteration, where the average number of steps decreases from 30 to 11. More modest, but still significant, improvement is seen for later iterations. Overall, the modified multitransmitter scheme reduces the total number of inner-loop iterations by a bit less than half, compared to Lanczos bi-diagonalization with explicit re-orthogonalization. 5 Discussion and Conclusions. Compared to standard CG schemes the proposed hybrid methods require substantially more storage, as the full sequence of data and model space vectors generated by the Lanczos process must be saved ( K ( M + N ) real numbers). Link Defunct: Piggott imposto em aposta esportiva - Japanese Mythology Mayo and Ray - Mythical Birds and Beasts from Many Lands Dragons of the Far East Mythological Dragon List. Ate que horas posso apostar na mega sena online.Casa Flamingo is, by far, the best beach rental home on IOP! Our 2nd year in a row staying in this wonderful home and it continues to be improved each season.
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A sensible data-weighting scheme is essential to recover the full information of all inverted components. If the inversion scheme penalizes deviations from a prior model, the set-up of the prior model has to be handled carefully and a range of prior models should be tested. Gary D. Egbert, Hybrid conjugate gradient-Occam algorithms for inversion of multifrequency and multitransmitter EM data, Geophysical Journal International , Volume 190, Issue 1, August 2012, Pages 255–266, https://doi.org/10.1111/j.1365-246X.2012.05523.x. Navbar Search Filter Enter search term Search. We describe novel hybrid algorithms for inversion of electromagnetic geophysical data, combining the computational and storage efficiency of a conjugate gradient approach with an Occam scheme for regularization and step-length control. The basic algorithm is based on the observation that iterative solution of the symmetric (Gauss-Newton) normal equations with conjugate gradients effectively generates a sequence of sensitivities for different linear combinations of the data, allowing construction of the Jacobian for a projection of the original full data space. The Occam scheme can then be applied to this projected problem, with the tradeoff parameter chosen by assessing fit to the full data set. For EM geophysical problems with multiple transmitters (either multiple frequencies or source geometries) an extension of the basic hybrid algorithm is possible. In this case multiple forward and adjoint solutions (one each for each transmitter) are required for each step in the iterative normal equation solver, and each corresponds to the sensitivity for a separate linear combination of data. From the perspective of the hybrid approach, with conjugate gradients generating an approximation to the full Jacobian, it is advantageous to save all of the component sensitivities, and use these to solve the projected problem in a larger subspace.
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