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However, in [35], the boundary information is also represented by the classical gradient.
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Then the optimization problem with color channel constraints is solved by using the classical gradient technique.
We first start by reviewing the classical gradient flow (also known as imaginary time (IMT)) method which considers the problem from the PDE standpoint, leading to numerically solve a dissipative equation.
As a demonstrative example, the discrete weak gradient operator is employed as a building block in the design of numerical schemes for a second order elliptic problem, in which the classical gradient operator is replaced by the discrete weak gradient.
These discrete weak gradients are used to approximate the classical gradient when solving the Darcy equation.
Both methods give results much better than the classical gradient optimization method.
The relaxed CQ algorithm [4] can be seen as a special case of the classical gradient projection method (GPM).
The multislope approach reveals less expensive and potentially more accurate than the classical gradient techniques.
When letting α=1, then model (1) degrades to the classical gradient fidelity model as used in [12, 13, 15].
An extensive experimental study shows undoubted advantages of the DREM-based frequency estimator in comparison to the classical gradient approach.
Based on the sensitivity analysis of the lower-level LSDP problem, the upper level programs are then solved by employing the classical gradient-based nonlinear optimization algorithms.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com