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Our forward operator refrains from any equifocal assumptions and fits well into a variational framework.
Including pitch angle deviations into the reconstruction leads to a nonlinear forward operator.
with ∇H the linear tangent of the forward operator and R the observation error covariance matrix.
For scalar data, (mathbf {G}) is the forward operator linearized around the present model.
(e o the observation errors, H the forward operator, see below).
Fig. 5 Singular values of the forward operator for the base model in descending order.
Similar(27)
He compares their convergence rates based on their forward operators, Fs, Fg, Fc.
Examples include the push-forward operator associated with a quasi-Anosov diffeomorphism or flow.
One defines the forward jump operator the backward jump operator and the graininess by (21).
For and, define the forward jump operator and backward jump operator, respectively, by (2.1).
The forward jump operator, the backward jump operator, and the graininess are defined, respectively, by (2.1).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com