Littérature scientifique sur le sujet « Linear estimation problems »
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Articles de revues sur le sujet "Linear estimation problems"
Florens, Jean-Pierre, et Anna Simoni. « REGULARIZING PRIORS FOR LINEAR INVERSE PROBLEMS ». Econometric Theory 32, no 1 (6 novembre 2014) : 71–121. http://dx.doi.org/10.1017/s0266466614000796.
Texte intégraldel Álamo, Miguel, et Axel Munk. « Total variation multiscale estimators for linear inverse problems ». Information and Inference : A Journal of the IMA 9, no 4 (2 mars 2020) : 961–86. http://dx.doi.org/10.1093/imaiai/iaaa001.
Texte intégralRoss, G. J. S. « Estimation problems of non-linear functional relationships ». Journal of Applied Statistics 17, no 3 (janvier 1990) : 299–306. http://dx.doi.org/10.1080/02664769000000002.
Texte intégralKoo, Ja-Yong, et Han-Yeong Chung. « Log-density estimation in linear inverse problems ». Annals of Statistics 26, no 1 (février 1998) : 335–62. http://dx.doi.org/10.1214/aos/1030563989.
Texte intégralVolaufová, Júlia. « Some estimation problems in multistage linear models ». Linear Algebra and its Applications 388 (septembre 2004) : 389–97. http://dx.doi.org/10.1016/j.laa.2004.03.007.
Texte intégralAdjali, M. H., et M. Laurent. « Thermal conductivity estimation in non-linear problems ». International Journal of Heat and Mass Transfer 50, no 23-24 (novembre 2007) : 4623–28. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2007.03.005.
Texte intégralRan, Mengfei, et Yihe Yang. « Optimal Estimation of Large Functional and Longitudinal Data by Using Functional Linear Mixed Model ». Mathematics 10, no 22 (17 novembre 2022) : 4322. http://dx.doi.org/10.3390/math10224322.
Texte intégralODEN, J. TINSLEY, SERGE PRUDHOMME, TIM WESTERMANN, JON BASS et MARK E. BOTKIN. « ERROR ESTIMATION OF EIGENFREQUENCIES FOR ELASTICITY AND SHELL PROBLEMS ». Mathematical Models and Methods in Applied Sciences 13, no 03 (mars 2003) : 323–44. http://dx.doi.org/10.1142/s0218202503002520.
Texte intégralС. И., Носков,, et Базилевский, М. П. « Multiple Lv-estimation of Linear Regression Models ». Успехи кибернетики / Russian Journal of Cybernetics, no 4(12) (28 décembre 2022) : 32–40. http://dx.doi.org/10.51790/2712-9942-2022-3-4-04.
Texte intégralEndtmayer, Bernhard, Ulrich Langer et Thomas Wick. « Multigoal-oriented error estimates for non-linear problems ». Journal of Numerical Mathematics 27, no 4 (18 décembre 2019) : 215–36. http://dx.doi.org/10.1515/jnma-2018-0038.
Texte intégralThèses sur le sujet "Linear estimation problems"
Edlund, Ove. « Solution of linear programming and non-linear regression problems using linear M-estimation methods / ». Luleå, 1999. http://epubl.luth.se/1402-1544/1999/17/index.html.
Texte intégralPIEROPAN, MIRKO. « Expectation Propagation Methods for Approximate Inference in Linear Estimation Problems ». Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2918002.
Texte intégralKaperick, Bryan James. « Diagonal Estimation with Probing Methods ». Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/90402.
Texte intégralMaster of Science
In the past several decades, as computational resources increase, a recurring problem is that of estimating certain properties very large linear systems (matrices containing real or complex entries). One particularly important quantity is the trace of a matrix, defined as the sum of the entries along its diagonal. In this thesis, we explore a problem that has only recently been studied, in estimating the diagonal entries of a particular matrix explicitly. For these methods to be computationally more efficient than existing methods, and with favorable convergence properties, we require the matrix in question to have a majority of its entries be zero (the matrix is sparse), with the largest-magnitude entries clustered near and on its diagonal, and very large in size. In fact, this thesis focuses on a class of methods called probing methods, which are of particular efficiency when the matrix is not known explicitly, but rather can only be accessed through matrix vector multiplications with arbitrary vectors. Our contribution is new analysis of these diagonal probing methods which extends the heavily-studied trace estimation problem, new applications for which probing methods are a natural choice for diagonal estimation, and a new class of deterministic probing methods which have favorable properties for large parallel computing architectures which are becoming ever-more-necessary as problem sizes continue to increase beyond the scope of single processor architectures.
Schülke, Christophe. « Statistical physics of linear and bilinear inference problems ». Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCC058.
Texte intégralThe recent development of compressed sensing has led to spectacular advances in the under standing of sparse linear estimation problems as well as in algorithms to solve them. It has also triggered anew wave of developments in the related fields of generalized linear and bilinear inference problems. These problems have in common that they combine a linear mixing step and a nonlinear, probabilistic sensing step, producing indirect measurements of a signal of interest. Such a setting arises in problems such as medical or astronomical Imaging. The aim of this thesis is to propose efficient algorithms for this class of problems and to perform their theoretical analysis. To this end, it uses belief propagation, thanks to which high-dimensional distributions can be sampled efficiently, thus making a bayesian approach to inference tractable. The resulting algorithms undergo phase transitions that can be analyzed using the replica method, initially developed in statistical physics of disordered systems. The analysis reveals phases in which inference is easy, hard or impossible, corresponding to different energy landscapes of the problem. The main contributions of this thesis can be divided into three categories. First, the application of known algorithms to concrete problems : community detection, superposition codes and an innovative imaging system. Second, a new, efficient message-passing algorithm for blind sensor calibration, that could be used in signal processing for a large class of measurement systems. Third, a theoretical analysis of achievable performances in matrix compressed sensing and of instabilities in bayesian bilinear inference algorithms
Mattavelli, Marco Mattavelli Marco Mattavelli Marco. « Motion analysis and estimation : from III-posed discrete linear inverse problems to MPEG-2 coding / ». Lausanne, 1997. http://library.epfl.ch/theses/?nr=1596.
Texte intégralBarbier, Jean. « Statistical physics and approximate message-passing algorithms for sparse linear estimation problems in signal processing and coding theory ». Sorbonne Paris Cité, 2015. http://www.theses.fr/2015USPCC130.
Texte intégralThis thesis is interested in the application of statistical physics methods and inference to signal processing and coding theory, more precisely, to sparse linear estimation problems. The main tools are essentially the graphical models and the approximate message-passing algorithm together with the cavity method (referred as the state evolution analysis in the signal processing context) for its theoretical analysis. We will also use the replica method of statistical physics of disordered systems which allows to associate to the studied problems a cost function referred as the potential of free entropy in physics. It allows to predict the different phases of typical complexity of the problem as a function of external parameters such as the noise level or the number of measurements one has about the signal: the inference can be typically easy, hard or impossible. We will see that the hard phase corresponds to a regime of coexistence of the actual solution together with another unwanted solution of the message passing equations. In this phase, it represents a metastable state which is not the true equilibrium solution. This phenomenon can be linked to supercooled water blocked in the liquid state below its freezing critical temperature. Thanks to this understanding of blocking phenomenon of the algorithm, we will use a method that allows to overcome the metastability mimicing the strategy adopted by nature itself for supercooled water: the nucleation and spatial coupling. In supercooled water, a weak localized perturbation is enough to create a crystal nucleus that will propagate in all the medium thanks to the physical couplings between closeby atoms. The same process will help the algorithm to find the signal, thanks to the introduction of a nucleus containing local information about the signal. It will then spread as a "reconstruction wave" similar to the crystal in the water. After an introduction to statistical inference and sparse linear estimation, we will introduce the necessary tools. Then we will move to applications of these notions. They will be divided into two parts. The signal processing part will focus essentially on the compressed sensing problem where we seek to infer a sparse signal from a small number of linear projections of it that can be noisy. We will study in details the influence of structured operators instead of purely random ones used originally in compressed sensing. These allow a substantial gain in computational complexity and necessary memory allocation, which are necessary conditions in order to work with very large signals. We will see that the combined use of such operators with spatial coupling allows the implementation of an highly optimized algorithm able to reach near to optimal performances. We will also study the algorithm behavior for reconstruction of approximately sparse signals, a fundamental question for the application of compressed sensing to real life problems. A direct application will be studied via the reconstruction of images measured by fluorescence microscopy. The reconstruction of "natural" images will be considered as well. In coding theory, we will look at the message-passing decoding performances for two distincts real noisy channel models. A first scheme where the signal to infer will be the noise itself will be presented. The second one, the sparse superposition codes for the additive white Gaussian noise channel is the first example of error correction scheme directly interpreted as a structured compressed sensing problem. Here we will apply all the tools developed in this thesis for finally obtaining a very promising decoder that allows to decode at very high transmission rates, very close of the fundamental channel limit
Krishnan, Rajet. « Problems in distributed signal processing in wireless sensor networks ». Thesis, Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1351.
Texte intégralKontak, Max [Verfasser]. « Novel algorithms of greedy-type for probability density estimation as well as linear and nonlinear inverse problems / Max Kontak ». Siegen : Universitätsbibliothek der Universität Siegen, 2018. http://d-nb.info/1157094554/34.
Texte intégralPester, Cornelia. « A posteriori error estimation for non-linear eigenvalue problems for differential operators of second order with focus on 3D vertex singularities ». Doctoral thesis, Berlin Logos-Verl, 2006. http://deposit.ddb.de/cgi-bin/dokserv?id=2806614&prov=M&dok_var=1&dok_ext=htm.
Texte intégralPester, Cornelia. « A posteriori error estimation for non-linear eigenvalue problems for differential operators of second order with focus on 3D vertex singularities ». Doctoral thesis, Logos Verlag Berlin, 2005. https://monarch.qucosa.de/id/qucosa%3A18520.
Texte intégralLivres sur le sujet "Linear estimation problems"
Kontoghiorghes, Erricos John. Parallel algorithms for linear models : Numerical methods and estimation problems. Boston : Kluwer Academic, 2000.
Trouver le texte intégralHesselager, Ole. On the application of bootstrap in some empirical linear bayes estimation problems. Copenhagen : University of Copenhagen, 1988.
Trouver le texte intégralPester, Cornelia. A posteriori error estimation for non-linear eigenvalue problems for differential operators of second order with focus on 3D vertex singularities. Berlin : Logos-Verl., 2006.
Trouver le texte intégralM, Milanese, dir. Bounding approaches to system identification. New York : Plenum Press, 1996.
Trouver le texte intégral1975-, Sims Robert, et Ueltschi Daniel 1969-, dir. Entropy and the quantum II : Arizona School of Analysis with Applications, March 15-19, 2010, University of Arizona. Providence, R.I : American Mathematical Society, 2011.
Trouver le texte intégralParallel Algorithms for Linear Models : Numerical Methods and Estimation Problems. Springer, 2011.
Trouver le texte intégralKontoghiorghes, Erricos. Parallel Algorithms for Linear Models : Numerical Methods and Estimation Problems. Springer London, Limited, 2012.
Trouver le texte intégralCardot, Hervé, et Pascal Sarda. Functional Linear Regression. Sous la direction de Frédéric Ferraty et Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.2.
Texte intégralNakonechnyi, Oleksandr, et Yuri Podlipenko. Guaranteed Estimation Problems in the Theory of Linear Ordinary Differential Equations with Uncertain Data. River Publishers, 2021.
Trouver le texte intégralNakonechnyi, Oleksandr, et Yuri Podlipenko. Guaranteed Estimation Problems in the Theory of Linear Ordinary Differential Equations with Uncertain Data. River Publishers, 2022.
Trouver le texte intégralChapitres de livres sur le sujet "Linear estimation problems"
Grafarend, Erik W., et Joseph L. Awange. « Special Problems of Algebraic Regression and Stochastic Estimation ». Dans Linear and Nonlinear Models, 493–525. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22241-2_14.
Texte intégralGriffith, Daniel A., et Jean H. P. Paelinck. « Linear Expenditure Systems and Related Estimation Problems ». Dans Advanced Studies in Theoretical and Applied Econometrics, 201–13. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72553-6_17.
Texte intégralGrafarend, Erik, Silvelyn Zwanzig et Joseph Awange. « Special Problems of Algebraic Regression and Stochastic Estimation ». Dans Applications of Linear and Nonlinear Models, 499–531. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94598-5_14.
Texte intégralPillonetto, Gianluigi, Tianshi Chen, Alessandro Chiuso, Giuseppe De Nicolao et Lennart Ljung. « Regularization in Reproducing Kernel Hilbert Spaces for Linear System Identification ». Dans Regularized System Identification, 247–311. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95860-2_7.
Texte intégralDobra, Adrian, Stephen E. Fienberg, Alessandro Rinaldo, Aleksandra Slavkovic et Yi Zhou. « Algebraic Statistics and Contingency Table Problems : Log-Linear Models, Likelihood Estimation, and Disclosure Limitation ». Dans Emerging Applications of Algebraic Geometry, 63–88. New York, NY : Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-09686-5_3.
Texte intégralNakonechnyi, O., et Y. Podlipenko. « Guaranteed Estimation of Parameters of Boundary Value Problems for Linear Ordinary Differential Equations with General Boundary Data ». Dans Guaranteed Estimation Problems in the Theory of Linear Ordinary Differential Equations with Uncertain Data, 163–216. New York : River Publishers, 2022. http://dx.doi.org/10.1201/9781003338369-4.
Texte intégralNakonechnyi, O., et Y. Podlipenko. « Guaranteed Estimation of Unknown Solutions and Right-Hand Sides of First Order Linear Systems of Periodic ODEs ». Dans Guaranteed Estimation Problems in the Theory of Linear Ordinary Differential Equations with Uncertain Data, 79–102. New York : River Publishers, 2022. http://dx.doi.org/10.1201/9781003338369-2.
Texte intégralNakonechnyi, O., et Y. Podlipenko. « Guaranteed Estimation of Solutions of Boundary Value Problems for Linear Ordinary Differential Equations with Decomposed Boundary Data ». Dans Guaranteed Estimation Problems in the Theory of Linear Ordinary Differential Equations with Uncertain Data, 103–62. New York : River Publishers, 2022. http://dx.doi.org/10.1201/9781003338369-3.
Texte intégralNakonechnyi, O., et Y. Podlipenko. « Guaranteed Estimates of Solutions and Right-Hand Sides of the Cauchy Problem Under Incomplete Data ». Dans Guaranteed Estimation Problems in the Theory of Linear Ordinary Differential Equations with Uncertain Data, 5–77. New York : River Publishers, 2022. http://dx.doi.org/10.1201/9781003338369-1.
Texte intégralKorotov, Sergey, Pekka Neittaanmäki et Sergey Repin. « A Posteriori Error Estimation in Terms of Linear Functionals for Boundary Value Problems of Elliptic Type ». Dans Numerical Mathematics and Advanced Applications, 587–95. Berlin, Heidelberg : Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18775-9_56.
Texte intégralActes de conférences sur le sujet "Linear estimation problems"
Van Wijk, K., J. A. Scales et W. Navidi. « Uncertainty Estimation and Error Analysis for Linear Inversion Problems ». Dans 63rd EAGE Conference & Exhibition. European Association of Geoscientists & Engineers, 2001. http://dx.doi.org/10.3997/2214-4609-pdb.15.n-33.
Texte intégralFuhrmann, Daniel R. « One-step optimal measurement selection for linear gaussian estimation problems ». Dans 2007 International Waveform Diversity and Design Conference. IEEE, 2007. http://dx.doi.org/10.1109/wddc.2007.4339415.
Texte intégralAnnaswamy, A. M., C. Thanomsat, N. R. Mehta et A. P. Loh. « A New Approach to Estimation of Nonlinear Parametrization in Dynamic Systems ». Dans ASME 1997 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/imece1997-0398.
Texte intégralIkami, Daiki, Toshihiko Yamasaki et Kiyoharu Aizawa. « Fast and Robust Estimation for Unit-Norm Constrained Linear Fitting Problems ». Dans 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2018. http://dx.doi.org/10.1109/cvpr.2018.00850.
Texte intégralSuliman, Mohamed A., Houssem Sifaou, Tarig Ballal, Mohamed-Slim Alouini et Tareq Y. Al-Naffouri. « Robust Estimation in Linear ILL-Posed Problems with Adaptive Regularization Scheme ». Dans ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018. http://dx.doi.org/10.1109/icassp.2018.8462651.
Texte intégralIto, Yoshimichi, Katsumi Irie et Shun Otsuka. « Estimation of geometric parameters in 3D reconstruction problems using linear matrix inequalities ». Dans 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS). IEEE, 2014. http://dx.doi.org/10.1109/scis-isis.2014.7044790.
Texte intégralVolkov, Vasiliy, et Dmitriy Demyanov. « Optimal Estimation of the Linear Functional of State Variables of a Dynamic System ». Dans 2019 XXI International Conference Complex Systems : Control and Modeling Problems (CSCMP). IEEE, 2019. http://dx.doi.org/10.1109/cscmp45713.2019.8976873.
Texte intégralLiu, Zhaoqiang, et Jun Han. « Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors ». Dans Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California : International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/454.
Texte intégralHill, David C. « Identification of Gas Turbine Dynamics : Time-Domain Estimation Problems ». Dans ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/97-gt-031.
Texte intégralChubich, Vladimir M., et Alina E. Prokofeva. « The Application of Robust Estimation to Active Parametric Identification of Stochastic Linear Discrete Systems ». Dans 2018 XIV International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering (APEIE). IEEE, 2018. http://dx.doi.org/10.1109/apeie.2018.8545985.
Texte intégralRapports d'organisations sur le sujet "Linear estimation problems"
Hou, Elizabeth Mary, et Earl Christopher Lawrence. Variational Methods for Posterior Estimation of Non-linear Inverse Problems. Office of Scientific and Technical Information (OSTI), septembre 2018. http://dx.doi.org/10.2172/1475317.
Texte intégralAyoul-Guilmard, Q., F. Nobile, S. Ganesh, M. Nuñez, R. Tosi, C. Soriano et R. Rosi. D5.5 Report on the application of multi-level Monte Carlo to wind engineering. Scipedia, 2022. http://dx.doi.org/10.23967/exaqute.2022.3.03.
Texte intégralSearcy, Stephen W., et Kalman Peleg. Adaptive Sorting of Fresh Produce. United States Department of Agriculture, août 1993. http://dx.doi.org/10.32747/1993.7568747.bard.
Texte intégralMayfield, Colin. Capacity Development in the Water Sector : the case of Massive Open On-line Courses. United Nations University Institute for Water, Environment and Health, janvier 2017. http://dx.doi.org/10.53328/mwud6984.
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