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With two extra regularization terms, this final energy minimization problem is converted to solve a level set evolution equation by using the gradient descent method.
For the geolocation approach proposed in this paper, a deviation is introduced to the landmark, and in combination with estimated relative delay between landmarks and the target, the target IP geolocation is converted to solve an optimization problem.
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And by using the cone complementarity linearization iterative algorithm, the fault detection filter design is converted to solving a sequence of convex optimization problems subject to LMIs.
However, surface machining error is affected mainly by cutting depth, so the ultimate goal of an iterative solution can be converted to solve the actual cutting depth U n at each nominal cutting tool position point, so that the actual cutting tool position coincides with the nominal cutting tool position or meets the given convergence conditions.
From the above analysis, the consistency problem can be converted to solving the feasibility problem with BMI (bilinear matrix inequality) constraints as: left{ begin{aligned} & hbox{min} ;t & {text{s.t.}} - {varvec{L}}({varvec{P}}_{ij} ) < t{varvec{I}} & {varvec{B}}left( {{varvec{P}}_{ij},{varvec{K}}_{ij} } right) < t{varvec{I}}end{aligned} right.
The boundary stabilization problem is converted to a problem of solving a specific Klein Gordon-type linear hyperbolic PDE.
A generalization of all these problems is considered, and each single problem is converted to the generalized version, then solved with the same LNS method.
In our MFE framework, solving the eigenvalue problem is converted to doing a series of integral iterations and eigenvalue solving in the coarsest mesh.
The STATCOM parameter tuning problem is converted to an optimization problem which is solved by ICA.
The PSSs parameter tuning problem is converted to an optimization problem which is solved by BAT search algorithm.
The PSSs parameters tuning problem is converted to an optimization problem which is solved by a chaotic optimization algorithm based on Lozi map.
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