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An algorithm to solve equality constrained optimization problems based on stabilized sequential quadratic programming, augmented Lagrangian and inexact restoration methods is presented. This formulation has attractive features in the sense that no constraint qualifications are needed at the limit point, and that it overcomes ill-conditioning of the… (More)

Data assimilation is the process of feeding a partially unknown prediction model with available information from observations, with the objective of correcting and improving the modeled results. One of the most important mathematical tools to perform data assimilation is the Kalman filter. This is essentially a predictor-corrector algorithm that is optimal… (More)

In this paper we present a method for estimating unknown parameters that appear on an avascular, spheric tumour growth model. The model for the tumour is based on nutrient driven growth of a continuum of live cells, whose birth and death generate volume changes described by a velocity field. The model consists on a coupled system of partial differential… (More)

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