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  • Didier Auroux - Publication list

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    Habilitation ThesisPhD ThesisBook chaptersArticlesProceedingsResearch reports

    Habilitation Thesis

    1. D. Auroux. Fast algorithms for image processing and data assimilation. Habilitation à Diriger des Recherches (Habilitation Thesis), University of Toulouse, France, November 2008.
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    PhD Thesis

    1. D. Auroux. Étude de quelques méthodes d'assimilation de données pour l'environnement. Ph.D. Thesis, Université de Nice Sophia-Antipolis, 2003.
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    Book chapters

    1. D. Auroux, J. Blum, and G. Ruggiero. Data assimilation for geophysical fluids: the Diffusive Back and Forth Nudging, pp. 139–174, INdAM Series 15, Springer, 2016.
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    2. Y. Parte, D. Auroux, J. Clément, M. Masmoudi, and J. Hermetz. Collaborative optimization, pp. 321–368, Multidisciplinary design optimization in computational mechanics, Wiley-ISTE, April 2010.
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    3. D. Auroux, J. Clément, J. Hermetz, M. Masmoudi, and Y. Parte. État de l'art et nouvelles tendances en conception collaborative, Optimisation multidisciplinaire en mécanique 1, Hermes Science Publications, April 2009.
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    4. D. Auroux, M. Masmoudi, and L. Jaafar Belaid. Image restoration and classification by topological asymptotic expansion, pp. 23–42, Variational Formulations in Mechanics: Theory and Applications, E. Taroco, E.A. de Souza Neto and A.A. Novotny (Eds), CIMNE, Barcelona, Spain, 2007.
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    5. D. Auroux and J. Blum. Data assimilation methods for an oceanographic problem, pp. 179–194, Lecture Notes - Mathematics in Industry XVI, Springer-Verlag, 2004.
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    Articles

    1. A. Apte, D. Auroux, and M. Ramaswamy. Observers for compressible Navier-Stokes equation. SIAM J. Control Optim., pp. 24 p., 2017. in press
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    2. D. Auroux. Data assimilation for geophysical fluids. Ann. Fac. Sci. Toulouse, 2017. in press
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    3. D. Auroux and V. Groza. Optimal parameters identification and sensitivity study for abrasive waterjet milling model. Inv. Prob. Sci. Eng., pp. 1560–1576, 2017.
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    4. D. Auroux and V. Groza. Sensitivity studies and parameter identification for noisy 3D moving AWJM model. Int. J. Eng. Math., pp. 1–15, 2016.
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    5. G. A. Ruggiero, Y. Ourmières, E. Cosme, J. Blum, D. Auroux, and J. Verron. Data assimilation experiments using the diffusive back and forth nudging for the NEMO ocean model. Nonlin. Proc. Geophys., 22:233–248, 2015.
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    6. D. Auroux, P. Bansart, and J. Blum. An evolution of the Back and Forth Nudging for geophysical data assimilation: application to Burgers equation and comparisons. Inv. Prob. Sci. Eng., 21(3):399–419, 2013.
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    7. D. Auroux and M. Nodet. The back and forth nudging algorithm for data assimilation problems: theoretical results on transport equations. ESAIM Control Optim. Calc. Var., 18(2):318–342, 2012.
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    8. E. Cosme, J. Verron, P. Brasseur, J. Blum, and D. Auroux. Smoothing problems in a Bayesian framework and their linear Gaussian solutions. Month. Weath. Rev., 140(2):683–695, 2012.
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    9. D. Auroux, J. Blum, and M. Nodet. Diffusive Back and Forth Nudging algorithm for data assimilation. C. R. Acad. Sci. Paris, Ser. I, 349(15-16):849–854, 2011.
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    10. D. Auroux and S. Bonnabel. Symmetry-based observers for some water-tank problems. IEEE Trans. Automat. Contr., 56(5):1046–1058, 2011.
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    11. D. Auroux and J. Fehrenbach. Identification of velocity fields for geophysical fluids from a sequence of images. Exp. Fluids, 50(2):313–328, 2011.
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    12. D. Auroux, L. D. Cohen, and M. Masmoudi. Contour detection and completion for inpainting and segmentation based on topological gradient and fast marching algorithms. Int. J. Biomed. Imaging, 2011. DOI:10.1155/2011/592924.
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    13. J.-C. Yakoubsohn, M. Masmoudi, G. Chèze, and D. Auroux. Approximate GCD a la Dedieu. Appl. Math. E-Notes, 11:244–248, 2011.
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    14. D. Auroux, L. Jaafar Belaid, and B. Rjaibi. Application of the topological gradient method to color image restoration. SIAM J. Imaging Sci., 3(2):153–175, 2010.
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    15. D. Auroux and M. Masmoudi. Image processing by topological asymptotic expansion. J. Math. Imaging Vision, 33(2):122–134, 2009.
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    16. D. Auroux. From restoration by topological gradient to medical image segmentation via an asymptotic expansion. Math. Comput. Model., 49(11-12):2191–2205, 2009.
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    17. D. Auroux. The back and forth nudging algorithm applied to a shallow water model, comparison and hybridization with the 4D-VAR. Int. J. Numer. Methods Fluids, 61(8):911–929, 2009.
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    18. D. Auroux and J. Blum. A nudging-based data assimilation method for oceanographic problems: the Back and Forth Nudging (BFN) algorithm. Nonlin. Proc. Geophys., 15:305–319, 2008.
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    19. M. Masmoudi, D. Auroux, and Y. Parte. The state of the art in Collaborative Design. Comput. Fluid Dyn. J., 2008. Accepted for publication.
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    20. D. Auroux. Generalization of the dual variational data assimilation algorithm to a nonlinear layered quasi-geostrophic ocean model. Inverse Problems, 23:2485–2503, 2007.
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    21. D. Auroux, L. Jaafar Belaid, and M. Masmoudi. A topological asymptotic analysis for the regularized grey-level image classification problem. Math. Model. Numer. Anal., 41(3):607–625, 2007.
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    22. D. Auroux. Several data assimilation methods for geophysical problems. Ind. J. Pure Appl. Math., 37(1):41–58, 2006.
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    23. D. Auroux and M. Masmoudi. A one-shot inpainting algorithm based on the topological asymptotic analysis. Comp. Appl. Math., 25(2-3):1–17, 2006.
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    24. D. Auroux and J. Blum. Back and forth nudging algorithm for data assimilation problems. C. R. Acad. Sci. Paris, Ser. I, 340:873–878, 2005.
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    25. D. Auroux and J. Blum. A dual data assimilation method for a layered quasi-geostrophic ocean model. Rev. R. Acad. Cien. Serie A Mat., 96(3):316–320, 2002.
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    26. F. Veersé, D. Auroux, and M. Fisher. Limited-memory BFGS diagonal preconditioners for a data assimilation problem in meteorology. Optim. Engineer., 1.3:323–339, 2000.
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    Proceedings

    1. D. Auroux, J. Blum, and M. Nodet. A new method for data assimilation: the Diffusive Back and Forth Nudging algorithm. In Proc. Int. Conf. Inverse Problems in Engineering (ICIPE), 2014.
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    2. A. Drogoul, G. Aubert, and D. Auroux. Topological gradient for a fourth order PDE and application to the detection of fine structures in 2D and 3D images. In IEEE International Conference on Image Processing 2014 (ICIP 2014), 2014.
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    3. D. Auroux, J. Blum, E. Cosme, Y. Ourmières, G. Ruggiero, and J. Verron. Data assimilation experiments using the Back and Forth Nudging and NEMO OGCM. In Proc. 6th World Meteorol. Org. Symp. Data Assimilation, 2013.
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    4. D. Auroux, J. Blum, and M. Nodet. A new method for data assimilation: the back and forth nudging algorithm. In MAMERN13: 5th International Conference on Approximation Methods and Numerical Modelling in Environment and Natural Resources, 2013.
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    5. D. Auroux, J. Blum, and S. Marinesque. Data assimilation: variational methods and back and forth nudging algorithm, application to thermoacoustic tomography. In Proc. 11th Int. Conf. Mathematical and Numerical Aspects of Waves, pp. 69–80, 2013.
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    6. Y. Ahipo, D. Auroux, L. D. Cohen, and M. Masmoudi. A hybrid scheme for contour detection and completion based on topological gradient and fast marching algorithms - Application to inpainting and segmentation. In Proc. SSVM 2011, 3rd Int. Conf. Scale Space Var. Methods Comput. Vision, pp. 386–397, 2012.
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    7. A. Apte, D. Auroux, and M. Ramaswamy. Variational data assimilation for discrete Burgers equation. In Proc. 8th UAB Conf. Diff. Eqns. and Comput. Simul., pp. 15–30, 19, Electron. J. Diff. Eqns., 2010.
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    8. D. Auroux, L. Jaafar Belaid, and B. Rjaibi. Application of the topological gradient method to tomography. In ARIMA Proc. TamTam'09, 2010.
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    9. D. Auroux and M. Masmoudi. Image processing by topological asymptotic analysis. In Mathematical Methods for Imaging and Inverse Problems, pp. 24–44, 26, ESAIM Proc., 2009.
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    10. D. Auroux. Extraction of velocity fields for geophysical fluids from a sequence of images. In Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing, pp. 961–964, 2009.
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    11. D. Auroux and J. Blum. The Back and Forth Nudging algorithm for oceanographic data assimilation. In Proc. WMODA 5, pp. 273.1–273.8, 2009.
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    12. D. Auroux, P. Bansart, and J. Blum. An easy-to-implement and efficient data assimilation method for the identification of the initial condition: the Back and Forth Nudging (BFN) algorithm. In Proc. Int. Conf. Inverse Problems in Engineering, 135, J. Phys.: Conf. Ser., 2008.
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    13. D. Auroux and M. Masmoudi. Image processing by topological asymptotic analysis. In Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing, pp. 777–780, 2008.
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    14. T. Touya and D. Auroux. Control and topological optimization of a large multibeam array antenna. In Proc. ARP 2008 - Antennas, Radar, and Wave Propagation, ACTA Press, 2008.
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    15. G. Caille, Y. Cailloce, C. Guiraud, D. Auroux, T. Touya, and M. Masmoudi. Large multibeam array antennas with reduced number of active chains. In Proc. EuCAP 2007 - Antennas and Propagation, pp. 142–150, 2007.
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    16. D. Auroux. Assimilation variationnelle de données océanographiques - Approches primale et duale. In Proc. Colloque Mathématiques et océanographie, pp. 147–159, 9(2), Annales Mathématiques Blaise Pascal, 2002.
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    Research reports

    1. D. Auroux. Assimilation de données en géophysique. Images des Mathématiques, Les échos de la recherche, 2014.
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    2. F. Veersé and D. Auroux. Some numerical experiments on scaling and updating L-BFGS diagonal preconditioners. Technical Report 3858, INRIA, 2000.
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