16 research outputs found

    On affine scaling inexact dogleg methods for bound-constrained nonlinear systems

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    Within the framework of affine scaling trust-region methods for bound constrained problems, we discuss the use of a inexact dogleg method as a tool for simultaneously handling the trust-region and the bound constraints while seeking for an approximate minimizer of the model. Focusing on bound-constrained systems of nonlinear equations, an inexact affine scaling method for large scale problems, employing the inexact dogleg procedure, is described. Global convergence results are established without any Lipschitz assumption on the Jacobian matrix, and locally fast convergence is shown under standard assumptions. Convergence analysis is performed without specifying the scaling matrix used to handle the bounds, and a rather general class of scaling matrices is allowed in actual algorithms. Numerical results showing the performance of the method are also given

    On affine scaling inexact dogleg methods for bound-constrained nonlinear systems

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    Within the framework of affine scaling trust-region methods for bound constrained problems, we discuss the use of a inexact dogleg method as a tool for simultaneously handling the trust-region and the bound constraints while seeking for an approximate minimizer of the model. Focusing on bound-constrained systems of nonlinear equations, an inexact affine scaling method for large scale problems, employing the inexact dogleg procedure, is described. Global convergence results are established without any Lipschitz assumption on the Jacobian matrix, and locally fast convergence is shown under standard assumptions. Convergence analysis is performed without specifying the scaling matrix used to handle the bounds, and a rather general class of scaling matrices is allowed in actual algorithms. Numerical results showing the performance of the method are also given

    Constrained dogleg methods for nonlinear systems with simple bounds

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    We focus on the numerical solution of medium scale bound-constrained systems of nonlinear equations. In this context, we consider an affine-scaling trust region approach that allows a great flexibility in choosing the scaling matrix used to handle the bounds. The method is based on a dogleg procedure tailored for constrained problems and so, it is named Constrained Dogleg method. It generates only strictly feasible iterates. Global and locally fast convergence is ensured under standard assumptions. The method has been implemented in the Matlab solver CoDoSol that supports several diagonal scalings in both spherical and elliptical trust region frameworks. We give a brief account of CoDoSol and report on the computational experience performed on a number of representative test problem

    MIMO CDMA-based Optical SATCOMs: A New Solution

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    A new scheme for MIMO CDMA-based optical satellite communications (OSATCOMs) is presented. Three independent problems are described for up-link and down- link in terms of two distinguished optimization problems. At first, in up-link, Pulse-width optimization is proposed to reduce dispersions over fibers as the terrestrial part. This is performed for return-to-zero (RZ) modulation that is supposed to be used as an example in here. This is carried out by solving the first optimization problem, while minimizing the probability of overlapping for the Gaussian pulses that are used to produce RZ. Some constraints are assumed such as a threshold for the peak-to-average power ratio (PAPR). In down-link, the second and the third problems are discussed as follows, jointly as a closed-form solution. Solving the second optimization problem, an objective function is obtained, namely the MIMO CDMA-based satellite weight-matrix as a conventional adaptive beam-former. The Satellite link is stablished over flat un-correlated Nakagami-m/Suzuki fading channels as the second problem. On the other hand, the mentioned optimization problem is robustly solved as the third important problem, while considering inter-cell interferences in the multi-cell scenario. Robust solution is performed due to the partial knowledge of each cell from the others in which the link capacity is maximized. Analytical results are conducted to investigate the merit of system.Comment: IEEE PCITC 2015 (15-17 Oct, India
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