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Summary

Descent methods of optimisation depend on calculating the derivatives of the composite function with respect to the large number of model parameters. Adjoint techniques allow the computation of derivatives in such complex models, with much less calculation than direct methods, and so enable practical non-linear inversion.Adjoint methods also allow effective computation of sensitivity kernels associated with the variation of critical parameters for both structure and sources. Sensitivity kernels can provide insight into the nature of Earth structure and the potential resolution of seismic tomography.

The adjoint method, recently introduced by Evans, is used to study obstacle problems,weakly coupled systems, cell problems for weakly coupled systems of Hamilton − Jacobiequations, and weakly coupled systems of obstacle type. In particular, new results aboutthe speed of convergence of some approximation procedures are derived.

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16 - Adjoint Methods and Sensitivity Analysis

Summary

Adjoint methods for obstacle problems and weakly coupledsystems of PDE

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2 results

16 - Adjoint Methods and Sensitivity Analysis

Summary

Adjoint methods for obstacle problems and weakly coupledsystems of PDE