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In this study, this design task is expressed as an optimization problem.
The proposed algorithm aims to minimize the H2 norm of the global estimation error dynamics, expressed as an optimization problem subject to Bilinear Matrix Inequality (BMI) constraints.
The proposed algorithm minimizes the H2 norm of the global estimation error dynamics, expressed as an optimization problem subject to Bilinear Matrix Inequality (BMI) constraints.
This design problem is expressed as an optimization problem using the desirability function, where the data generated by finite element analysis is converted to an artificial neural network model.
The controller tuning procedure was expressed as an optimization problem in which novel time-domain integrals of the weighted squared error and weighted squared control signals, with initial state zero and inputs not necessarily defined over the Lebesgue normed space (L2+), were minimized.
This can be expressed as an optimization problem, since the difference between the obtained throughput by simulations and the target throughput must be minimized.
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The problem of designing the controllers is mathematically expressed as a constrained optimization programming and solved by particle swarm optimization (PSO).
The optimization of the determinant of the Fisher information matrix is expressed as a convex optimization problem.
Different conceptions of bounded rationality are divided as to whether bounded rational behavior is thought to be fundamentally non-optimizing or whether it can be expressed as a (constrained) optimization problem and as to whether it involves any kind of meta-reasoning (Klein [2001]).
We show that the offline throughput maximization problem can be expressed as a convex optimization problem.
The GSM is also practical because learning the GSM is expressed as a convex optimization problem and the global solution can be found by existing algorithms.
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