Relevant bibliographies by topics / Smoothing problems

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Smoothing problems'

Author: Grafiati
Published: 6 September 2023
Last updated: 7 September 2023

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Journal articles on the topic "Smoothing problems"

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Cipra, Tomáš. "Some problems of exponential smoothing." Applications of Mathematics 34, no. 2 (1989): 161–69. http://dx.doi.org/10.21136/am.1989.104344.

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Asmuss, Svetlana, and Natalja Budkina. "ON SOME GENERALIZATION OF SMOOTHING PROBLEMS." Mathematical Modelling and Analysis 20, no. 3 (June 2, 2015): 311–28. http://dx.doi.org/10.3846/13926292.2015.1048756.

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The paper deals with the generalized smoothing problem in abstract Hilbert spaces. This generalized problem involves particular cases such as the interpolating problem, the smoothing problem with weights, the smoothing problem with obstacles, the problem on splines in convex sets and others. The theorem on the existence and characterization of a solution of the generalized problem is proved. It is shown how the theorem gives already known theorems in special cases as well as some new results.
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Yin, Hongxia. "An Adaptive Smoothing Method for Continuous Minimax Problems." Asia-Pacific Journal of Operational Research 32, no. 01 (February 2015): 1540001. http://dx.doi.org/10.1142/s0217595915400011.

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A simple and implementable two-loop smoothing method for semi-infinite minimax problem is given with the discretization parameter and the smoothing parameter being updated adaptively. We prove the global convergence of the algorithm when the steepest descent method or a BFGS type quasi-Newton method is applied to the smooth subproblems. The strategy for updating the smoothing parameter can not only guarantee the convergence of the algorithm but also considerably reduce the ill-conditioning caused by increasing the value of the smoothing parameter. Numerical tests show that the algorithm is robust and effective.
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Asmuss, Svetlana, and Natalia Budkina. "ON SMOOTHING PROBLEMS WITH ONE ADDITIONAL EQUALITY CONDITION." Mathematical Modelling and Analysis 14, no. 2 (June 30, 2009): 159–68. http://dx.doi.org/10.3846/1392-6292.2009.14.159-168.

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Two problems of approximation in Hilbert spaces are considered with one additional equality condition: the smoothing problem with a weight and the smoothing problem with an obstacle. This condition is a generalization of the equality, which appears in the problem of approximation of a histogram in a natural way. We characterize the solutions of these smoothing problems and investigate the connection between them.
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Zhou, Zhengyong, and Qi Yang. "An Active Set Smoothing Method for Solving Unconstrained Minimax Problems." Mathematical Problems in Engineering 2020 (June 24, 2020): 1–25. http://dx.doi.org/10.1155/2020/9108150.

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In this paper, an active set smoothing function based on the plus function is constructed for the maximum function. The active set strategy used in the smoothing function reduces the number of gradients and Hessians evaluations of the component functions in the optimization. Combing the active set smoothing function, a simple adjustment rule for the smoothing parameters, and an unconstrained minimization method, an active set smoothing method is proposed for solving unconstrained minimax problems. The active set smoothing function is continuously differentiable, and its gradient is locally Lipschitz continuous and strongly semismooth. Under the boundedness assumption on the level set of the objective function, the convergence of the proposed method is established. Numerical experiments show that the proposed method is feasible and efficient, particularly for the minimax problems with very many component functions.
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Yang, X. Q. "Smoothing approximations to nonsmooth optimization problems." Journal of the Australian Mathematical Society. Series B. Applied Mathematics 36, no. 3 (January 1995): 274–85. http://dx.doi.org/10.1017/s0334270000010444.

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AbstractWe study certain types of composite nonsmooth minimization problems by introducing a general smooth approximation method. Under various conditions we derive bounds on error estimates of the functional values of original objective function at an approximate optimal solution and at the optimal solution. Finally, we obtain second-order necessary optimality conditions for the smooth approximation prob lems using a recently introduced generalized second-order directional derivative.
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Tsar'kov, I. G. "Linear methods in some smoothing problems." Mathematical Notes 56, no. 6 (December 1994): 1255–70. http://dx.doi.org/10.1007/bf02266694.

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Haddou, Mounir, and Patrick Maheux. "Smoothing Methods for Nonlinear Complementarity Problems." Journal of Optimization Theory and Applications 160, no. 3 (September 12, 2013): 711–29. http://dx.doi.org/10.1007/s10957-013-0398-1.

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Zhu, Jianguang, and Binbin Hao. "A new smoothing method for solving nonlinear complementarity problems." Open Mathematics 17, no. 1 (March 10, 2019): 104–19. http://dx.doi.org/10.1515/math-2019-0011.

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Abstract In this paper, a new improved smoothing Newton algorithm for the nonlinear complementarity problem was proposed. This method has two-fold advantages. First, compared with the classical smoothing Newton method, our proposed method needn’t nonsingular of the smoothing approximation function; second, the method also inherits the advantage of the classical smoothing Newton method, it only needs to solve one linear system of equations at each iteration. Without the need of strict complementarity conditions and the assumption of P0 property, we get the global and local quadratic convergence properties of the proposed method. Numerical experiments show that the efficiency of the proposed method.
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Wang, Jian, LingLing Shen, LeSheng Jin, and Gang Qian. "Age Sequence Recursive Models for Long Time Evaluation Problems." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26, no. 02 (April 2018): 299–325. http://dx.doi.org/10.1142/s0218488518500162.

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The evaluation models for long time historical data is important in many applications. In this study, based on Age measure defined by Yager, we propose the definitions of Age Sequence and Age Series. Then, we provide a Generalized Recursive Smoothing method. Some classical smoothing models in evaluation problems can be seen as special cases of Generalized Recursive Smoothing method. In order to obtain more reasonable and effective aggregation results of the historical data, we propose some different Age Sequences, e.g., the Generalized Harmonic Age Sequence and p Age Sequence, which theoretically can provide infinite more recursive smoothing methods satisfying different preferences of decision makers.
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Dissertations / Theses on the topic "Smoothing problems"

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Eichmann, Katrin. "Smoothing stochastic bang-bang problems." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2013. http://dx.doi.org/10.18452/16799.

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Motiviert durch das Problem der optimalen Strategie beim Handel einer großen Aktienposition, behandelt diese Arbeit ein stochastisches Kontrollproblem mit zwei besonderen Eigenschaften. Zum einen wird davon ausgegangen, dass das Kontrollproblem eine exponentielle Verzögerung in der Kontrollvariablen beinhaltet, zum anderen nehmen wir an, dass die Koeffizienten des Kontrollproblems linear in der Kontrollvariablen sind. Wir erhalten ein degeneriertes stochastisches Kontrollproblem, dessen Lösung - sofern sie existiert - Bang-Bang-Charakter hat. Die resultierende Unstetigkeit der optimalen Kontrolle führt dazu, dass die Existenz einer optimalen Lösung nicht selbstverständlich ist und bewiesen werden muss. Es wird eine Folge von stochastischen Kontrollproblemen mit Zustandsprozessen konstruiert, deren jeweilige Diffusionsmatrix invertierbar ist und die ursprüngliche degenerierte Diffusionsmatrix approximiert. Außerdem stellen die Kostenfunktionale der Folge eine konvexe Approximation des ursprünglichen linearen Kostenfunktionals dar. Um die Konvergenz der Lösungen dieser Folge zu zeigen, stellen wir die Kontrollprobleme in Form von stochastischen Vorwärts-Rückwärts-Differential-gleichungen (FBSDEs) dar. Wir zeigen, dass die zu der konstruierten Folge von Kontrollproblemen gehörigen Lösungen der Vorwärts-Rückwärtsgleichungen – zumindest für eine Teilfolge - in Verteilung konvergieren. Mit Hilfe einer Konvexitätsannahme der Koeffizienten ist es möglich, einen Kontroll-prozess auf einem passenden Wahrscheinlichkeitsraum zu konstruieren, der optimal für das ursprüngliche stochastische Kontrollproblem ist. Neben der damit bewiesenen Existenz einer optimalen (Bang-Bang-) Lösung, wird damit auch eine glatte Approximation der unstetigen Bang-Bang-Lösung erreicht, welche man für die numerische Approximation des Problems verwenden kann. Die Ergebnisse werden schließlich dann in Form von numerischen Simulationen auf das Problem der optimalen Handels¬ausführung angewendet.
Motivated by the problem of how to optimally execute a large stock position, this thesis considers a stochastic control problem with two special properties. First, the control problem has an exponential delay in the control variable, and so the present value of the state process depends on the moving average of past control decisions. Second, the coefficients are assumed to be linear in the control variable. It is shown that a control problem with these properties generates a mathematically challenging problem. Specifically, it becomes a stochastic control problem whose solution (if one exists) has a bang-bang nature. The resulting discontinuity of the optimal solution creates difficulties in proving the existence of an optimal solution and in solving the problem with numerical methods. A sequence of stochastic control problems with state processes is constructed, whose diffusion matrices are invertible and approximate the original degenerate diffusion matrix. The cost functionals of the sequence of control problems are convex approximations of the original linear cost functional. To prove the convergence of the solutions, the control problems are written in the form of forward-backward stochastic differential equations (FBSDEs). It is then shown that the solutions of the FBSDEs corresponding to the constructed sequence of control problems converge in law, at least along a subsequence. By assuming convexity of the coefficients, it is then possible to construct from this limit an admissible control process which, for an appropriate reference stochastic system, is optimal for our original stochastic control problem. In addition to proving the existence of an optimal (bang-bang) solution, we obtain a smooth approximation of the discontinuous optimal bang-bang solution, which can be used for the numerical solution of the problem. These results are then applied to the optimal execution problem in form of numerical simulations.
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Herrick, David Richard Mark. "Wavelet methods for curve and surface estimation." Thesis, University of Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310601.

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Xu, Song. "Non-interior path-following methods for complementarity problems /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/5793.

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Lowe, Matthew. "Extended and Unscented Kalman Smoothing for Re-linearization of Nonlinear Problems with Applications." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-dissertations/457.

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The Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Ensemble Kalman Filter (EnKF) are commonly implemented practical solutions for solving nonlinear state space estimation problems; all based on the linear state space estimator, the Kalman Filter. Often, the UKF and EnKF are cited as a superior methods to the EKF with respect to error-based performance criteria. The UKF in turn has the advantage over the EnKF of smaller computational complexity. In practice however the UKF often fails to live up to this expectation, with performance which does not surpass the EKF and estimates which are not as robust as the EnKF. This work explores the geometry of alternative sigma point sets, which form the basis of the UKF, contributing several new sets along with novel methods used to generate them. In particular, completely novel systems of sigma points that preserve higher order statistical moments are found and evaluated. Additionally a new method for scaling and problem specific tuning of sigma point sets is introduced as well as a discussion of why this is necessary, and a new way of thinking about UKF systems in relation to the other two Kalman Filter methods. An Iterated UKF method is also introduced, similar to the smoothing iterates developed previously for the EKF. The performance of all of these methods is demonstrated using problem exemplars with the improvement of the contributed methods highlighted.
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Eichmann, Katrin [Verfasser], Peter [Akademischer Betreuer] Imkeller, Ying [Akademischer Betreuer] Hu, and Michael [Akademischer Betreuer] Kupper. "Smoothing stochastic bang-bang problems : with application to the optimal execution problem / Katrin Eichmann. Gutachter: Peter Imkeller ; Ying Hu ; Michael Kupper." Berlin : Humboldt Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2013. http://d-nb.info/1041284543/34.

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Klann, Esther. "Regularization of linear ill-posed problems in two steps : combination of data smoothing and reconstruction methods." kostenfrei, 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=979913039.

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Padoan, Simone. "Computational methods for complex problems in extreme value theory." Doctoral thesis, Università degli studi di Padova, 2008. http://hdl.handle.net/11577/3427194.

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Rare events are part of the real world but inevitably environmental extreme events may have a massive impact on everyday life. We are familiar, for example, with the consequences and damage caused by hurricanes and floods etc. Consequently, there is considerable attention in studying, understanding and predicting the nature of such phenomena and the problems caused by them, not least because of the possible link between extreme climate events and global warming or climate change. Thus the study of extreme events has become ever more important, both in terms of probabilistic and statistical research. This thesis aims to provide statistical modelling and methods for making inferences about extreme events for two types of process. First, non-stationary univariate processes; second, spatial stationary processes. In each case the statistical aspects focus on model fitting and parameter estimation with applications to the modelling of environmental processes including, in particular, nonstationary extreme temperature series and spatially recorded rainfall measures.
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Rau, Christian, and rau@maths anu edu au. "Curve Estimation and Signal Discrimination in Spatial Problems." The Australian National University. School of Mathematical Sciences, 2003. http://thesis.anu.edu.au./public/adt-ANU20031215.163519.

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In many instances arising prominently, but not exclusively, in imaging problems, it is important to condense the salient information so as to obtain a low-dimensional approximant of the data. This thesis is concerned with two basic situations which call for such a dimension reduction. The first of these is the statistical recovery of smooth edges in regression and density surfaces. The edges are understood to be contiguous curves, although they are allowed to meander almost arbitrarily through the plane, and may even split at a finite number of points to yield an edge graph. A novel locally-parametric nonparametric method is proposed which enjoys the benefit of being relatively easy to implement via a `tracking' approach. These topics are discussed in Chapters 2 and 3, with pertaining background material being given in the Appendix. In Chapter 4 we construct concomitant confidence bands for this estimator, which have asymptotically correct coverage probability. The construction can be likened to only a few existing approaches, and may thus be considered as our main contribution. ¶ Chapter 5 discusses numerical issues pertaining to the edge and confidence band estimators of Chapters 2-4. Connections are drawn to popular topics which originated in the fields of computer vision and signal processing, and which surround edge detection. These connections are exploited so as to obtain greater robustness of the likelihood estimator, such as with the presence of sharp corners. ¶ Chapter 6 addresses a dimension reduction problem for spatial data where the ultimate objective of the analysis is the discrimination of these data into one of a few pre-specified groups. In the dimension reduction step, an instrumental role is played by the recently developed methodology of functional data analysis. Relatively standar non-linear image processing techniques, as well as wavelet shrinkage, are used prior to this step. A case study for remotely-sensed navigation radar data exemplifies the methodology of Chapter 6.
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Yilmaz, Asim Egemen. "Finite Element Modeling Of Electromagnetic Scattering Problems Via Hexahedral Edge Elements." Phd thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608587/index.pdf.

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In this thesis, quadratic hexahedral edge elements have been applied to the three dimensional for open region electromagnetic scattering problems. For this purpose, a semi-automatic all-hexahedral mesh generation algorithm is developed and implemented. Material properties inside the elements and along the edges are also determined and prescribed during the mesh generation phase in order to be used in the solution phase. Based on the condition number quality metric, the generated mesh is optimized by means of the Particle Swarm Optimization (PSO) technique. A framework implementing hierarchical hexahedral edge elements is implemented to investigate the performance of linear and quadratic hexahedral edge elements. Perfectly Matched Layers (PMLs), which are implemented by using a complex coordinate transformation, have been used for mesh truncation in the software. Sparse storage and relevant efficient matrix ordering are used for the representation of the system of equations. Both direct and indirect sparse matrix solution methods are implemented and used. Performance of quadratic hexahedral edge elements is deeply investigated over the radar cross-sections of several curved or flat objects with or without patches. Instead of the de-facto standard of 0.1 wavelength linear element size, 0.3-0.4 wavelength quadratic element size was observed to be a new potential criterion for electromagnetic scattering and radiation problems.
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Audiard, Corentin. "Problèmes aux limites dispersifs linéaires non homogènes, application au système d’Euler-Korteweg." Thesis, Lyon 1, 2010. http://www.theses.fr/2010LYO10261/document.

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Le but principal de cette thèse est d'obtenir des résultats d'existence et d'unicité pour des équations aux dérivées partielles dispersives avec conditions aux limites non homogènes. L'approche privilégiée est l'adaptation de techniques issues de la théorie classique des problèmes aux limites hyperboliques (que l'on rappelle au chapitre 1, en améliorant légèrement un résultat). On met en évidence au chapitre 3 une classe d'équations linéaires qu'on peut qualifier de dispersives satisfaisant des critères “minimaux”, et des résultats d'existence et d'unicité pour le problème aux limites associé à celles-ci sont obtenus au chapitre 4.Le fil rouge du mémoire est le modèle d'Euler-Korteweg, pour lequel on aborde l'analyse du problème aux limites sur une version linéarisée au chapitre 2. Toujours pour cette version linéarisée, on prouve un effet Kato-régularisant au chapitre 3. Enfin l'analyse numérique du modèle est abordée au chapitre 5. Pour cela, on commence par utiliser les résultats précédents pour décrire une manière simple d'obtenir les conditions aux limites dites transparentes dans le cadre des équations précédemment décrites puis on utilise ces conditions aux limites pour le modèle d'Euler-Korteweg semi-linéaire afin d'observer la stabilité/instabilité des solitons, ainsi qu'un phénomène d'explosion en temps fini
The main aim of this thesis is to obtain well-posedness results for boundary value problems especially with non-homogeneous boundary conditions. The approach that we chose here is to adapt technics from the classical theory of hyperbolic boundary value problems (for which we give a brief survey in the first chapter, and a slight generalization). In chapter 3 we delimitate a class of linear dispersive equations, and we obtain well-posedness results for corresponding boundary value problems in chapter 4.The leading thread of this memoir is the Euler-Korteweg model. The boundary value problem for a linearized version is investigated in chapter 2, and the Kato-smoothing effect is proved (also for the linearized model) in chapter 3. Finally, the numerical analysis of the model is made in chapter 5. To begin with, we use the previous abstract results to show a simple way of deriving the so-called transparent boundary conditions for the equations outlined in chapter 3, and those conditions are then used to numerically solve the semi-linear Euler-Korteweg model. This allow us to observe the stability and instability of solitons, as well as a finite time blow up
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Books on the topic "Smoothing problems"

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Semenovich, Zavʹi͡a︡lov I͡U︡riĭ, Pavlov N. N, and Miroshnichenko V. L, eds. Ėkstremalʹnye svoĭstva splaĭnov i zadacha sglazhivanii͡a︡. Novosibirsk: Izd-vo "Nauka," Sibirskoe otd-nie, 1988.

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Hulett, Victoria L. Smoothies for kidney health: A delicious approach to the prevention and management of kidney problems & so much more. Garden City Park, NY: Square One Publishers, 2015.

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Ulbrich, Michael, Liqun Qi, and Defeng Sun. Semismooth and Smoothing Newton Methods. Springer, 2021.

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Ferraty, Frédéric, and Philippe Vieu. Kernel Regression Estimation for Functional Data. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.4.

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This article provides an overview of recent nonparametric and semiparametric advances in kernel regression estimation for functional data. In particular, it considers the various statistical techniques based on kernel smoothing ideas that have recently been developed for functional regression estimation problems. The article first examines nonparametric functional regression modelling before discussing three popular functional regression estimates constructed by means of kernel ideas, namely: the Nadaraya-Watson convolution kernel estimate, the kNN functional estimate, and the local linear functional estimate. Uniform asymptotic results are then presented. The article proceeds by reviewing kernel methods in semiparametric functional regression such as single functional index regression and partial linear functional regression. It also looks at the use of kernels for additive functional regression and concludes by assessing the impact of kernel methods on practical real-data analysis involving functional (curves) datasets.
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Delsol, Laurent. Nonparametric Methods for α-Mixing Functional Random Variables. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.5.

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This article considers how functional kernel methods can be used to study α-mixing datasets. It first provides an overview of how prediction problems involving dependent functional datasets may arise from the study of time series, focusing on the standard discretized model and modelization that takes into account the functional nature of the evolution of the quantity to be studied over time. It then considers strong mixing conditions, with emphasis on the notion of α-mixing coefficients and α-mixing variables introduced by Rosenblatt (1956). It also describes some conditions for a Markov chain to be α-mixing; some useful tools that provide covariance inequalities, exponential inequalities, and Central Limit Theorem (CLT) for α-mixing sequences; the asymptotic properties of functional kernel estimators; the use of kernel smoothing methods with α-mixing datasets; and various functional kernel estimators corresponding to different prediction methods. Finally, the article highlights some interesting prospects for further research.
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Karaman, Sadi. Fixed point smoothing algorithm to the torpedo tracking problem. 1986.

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Mabray, Beaulah. Weight Problems: How to Prepare a Perfect, Delicious Green Smoothie. Independently Published, 2022.

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Gravina, Francis. Green Smoothie Recipes for You : Get Rid of Your Indigestion Problems, Sleeping Issues: Vegan Meal Plan. Independently Published, 2021.

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Butz, Martin V., and Esther F. Kutter. Primary Visual Perception from the Bottom Up. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198739692.003.0008.

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This chapter addresses primary visual perception, detailing how visual information comes about and, as a consequence, which visual properties provide particularly useful information about the environment. The brain extracts this information systematically, and also separates redundant and complementary visual information aspects to improve the effectiveness of visual processing. Computationally, image smoothing, edge detectors, and motion detectors must be at work. These need to be applied in a convolutional manner over the fixated area, which are computations that are predestined to be solved by means of cortical columnar structures in the brain. On the next level, the extracted information needs to be integrated to be able to segment and detect object structures. The brain solves this highly challenging problem by incorporating top-down expectations and by integrating complementary visual information aspects, such as light reflections, texture information, line convergence information, shadows, and depth information. In conclusion, the need for integrating top-down visual expectations to form complete and stable perceptions is made explicit.
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QuickBooks® Pro Support+1(866∎751∎2963)Phone Number. mrinalt, 2022.

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Book chapters on the topic "Smoothing problems"

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Nason, Guy P., and Bernard W. Silverman. "Wavelets for Regression and Other Statistical Problems." In Smoothing and Regression, 159–91. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118150658.ch7.

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Gander, W., and Urs von Matt. "Smoothing Filters." In Solving Problems in Scientific Computing Using Maple and MATLAB®, 133–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18873-2_9.

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Gander, W., and U. von Matt. "Smoothing Filters." In Solving Problems in Scientific Computing Using Maple and Matlab ®, 121–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-97533-2_9.

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Gander, W., and U. von Matt. "Smoothing Filters." In Solving Problems in Scientific Computing Using Maple and MATLAB®, 121–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-97619-3_9.

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Gander, W., and U. von Matt. "Smoothing Filters." In Solving Problems in Scientific Computing Using Maple and MATLAB®, 135–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-97953-8_9.

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Bagirov, A. M., N. Sultanova, A. Al Nuaimat, and S. Taheri. "Solving Minimax Problems: Local Smoothing Versus Global Smoothing." In Numerical Analysis and Optimization, 23–43. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-90026-1_2.

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Enander, Rickard. "Improved Residual Smoothing." In Nonlinear Hyperbolic Problems: Theoretical, Applied, and Computational Aspects, 192–98. Wiesbaden: Vieweg+Teubner Verlag, 1993. http://dx.doi.org/10.1007/978-3-322-87871-7_23.

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Berry, Scott M., Raymond J. Carroll, and David Ruppert. "Bayesian Smoothing for Measurement Error Problems." In Total Least Squares and Errors-in-Variables Modeling, 121–30. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-017-3552-0_11.

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Rinott, Yosef, and Natalie Shlomo. "A smoothing model for sample disclosure risk estimation." In Complex Datasets and Inverse Problems, 161–71. Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2007. http://dx.doi.org/10.1214/074921707000000120.

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Chen, Xiaojun, Nami Matsunaga, and Tetsuro Yamamoto. "Smoothing Newton Methods for Nonsmooth Dirichlet Problems." In Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods, 65–79. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_4.

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Conference papers on the topic "Smoothing problems"

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LAMM, PATRICIA K. "VARIABLE SMOOTHING REGULARIZATION METHODS FOR INVERSE PROBLEMS." In Proceedings of the 6th IEEE Mediterranean Conference. WORLD SCIENTIFIC, 1999. http://dx.doi.org/10.1142/9789814447317_0055.

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"Alternative smoothing algorithms for on-line estimation problems." In 29th Aerospace Sciences Meeting. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1991. http://dx.doi.org/10.2514/6.1991-194.

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Lukasik, Michal, Himanshu Jain, Aditya Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix Yu, and Sanjiv Kumar. "Semantic Label Smoothing for Sequence to Sequence Problems." In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Stroudsburg, PA, USA: Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.emnlp-main.405.

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Grimble, M. J. "H/sub infinity / inferential filtering, prediction and smoothing problems." In Proceedings of ICASSP '93. IEEE, 1993. http://dx.doi.org/10.1109/icassp.1993.319535.

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Wu, Congwei, Jiping Cao, and Yahong Zhu. "A Smoothing Multidimensional Filter Method for Nonlinear Complementarity Problems." In 2016 International Conference on Computer Science and Electronic Technology. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/cset-16.2016.10.

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Zhang, Meng, Jianhua Tao, Huibin Jia, and Xia Wang. "Improving HMM Based Speech Synthesis by Reducing Over-Smoothing Problems." In 2008 6th International Symposium on Chinese Spoken Language Processing (ISCSLP). IEEE, 2008. http://dx.doi.org/10.1109/chinsl.2008.ecp.16.

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Goldman, Paul, and Agnes Muszynska. "Smoothing Technique for Rub or Looseness-Related Rotor Dynamic Problems." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0297.

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Abstract The lateral vibration response of a rotor, experiencing periodic contact with a nonrotating machine component, is considered. In the case of an inelastic impact, this causes a piecewise, step-changing stiffness of the system. Applying to the rotor model a specially developed variable transformation which smooths discontinuities, and applying then an averaging technique, a variety of imbalance-related resonant regimes of rotor lateral motion are obtained, and their stability is analyzed. The developed analytical algorithm has a high potential as a valuable research tool for investigating local nonlinear effects in rotor systems.
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Yousefian, Farzad, Angelia Nedic, and Uday V. Shanbhag. "Optimal robust smoothing extragradient algorithms for stochastic variational inequality problems." In 2014 IEEE 53rd Annual Conference on Decision and Control (CDC). IEEE, 2014. http://dx.doi.org/10.1109/cdc.2014.7040302.

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Tsvil, Mariya, Ella Guleva, and Margarita Zubkova. "ECONOMETRIC ANALYSIS OF THE VOLUME OF MUTUAL TRADE OF THE EAEU MEMBER STATES." In Economy of Russia: problems, trends, forecasts. au: AUS PUBLISHERS, 2021. http://dx.doi.org/10.26526/conferencearticle_61cc296bccac42.37597958.

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The article provides econometric time series models for the volumes of mutual trade of the EAEU member states based on quarterly data from the 1st quarter of 2017 to the 3rd quarter of 2021. An exponential smoothing model and a multiplicative model are built. Also, a forecast was made for the volume of mutual trade in the IV quarter of 2021
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Xavier, Vinicius, L., Felipe, M. G. França, Adilson, E. Xavier, and Priscila, M. V. Lima. "Fermat-weber location problem solving by the hyperbolic smoothing approach." In International Workshop of "Stochastic Programming for Implementation and Advanced Applications". The Association of Lithuanian Serials, 2012. http://dx.doi.org/10.5200/stoprog.2012.26.

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The solution of the Fermat-Weber Location Problem, also known as the continuous p-median problem, is considered by using the Hyperbolic Smoothing approach. For the purpose of illustrating both the reliability and the efficiency of the method, a set of computational experiments was performed, making use of traditional test problems described in the literature.
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Reports on the topic "Smoothing problems"

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Pee, E. Y., and J. O. Royset. On Solving Large-Scale Finite Minimax Problems using Exponential Smoothing. Fort Belvoir, VA: Defense Technical Information Center, January 2010. http://dx.doi.org/10.21236/ada518716.

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Elliott, Robert J. The Existence of Smooth Densities for the Prediction Filtering and Smoothing Problems. Fort Belvoir, VA: Defense Technical Information Center, November 1987. http://dx.doi.org/10.21236/ada189865.

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Royset, J. O., and E. Y. Pee. Rate of Convergence Analysis of Discretization and Smoothing Algorithms for Semi-Infinite Minimax Problems. Fort Belvoir, VA: Defense Technical Information Center, June 2011. http://dx.doi.org/10.21236/ada551990.

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Andrian, Leandro Gaston, Oscar Valencia, Jorge Hirs, and Ivan Leonardo Urrea Rios. Fiscal Rules and Economic Cycles: Quality (Always) Matters. Inter-American Development Bank, January 2023. http://dx.doi.org/10.18235/0004570.

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Governments can issue public debt for both good and bad reasons. The former include intertemporal tax smoothing, fiscal stimulus, and asset management. In contrast, the bad reasons, which generate higher indebtedness, are mainly associated with political cycles, rent capture, intergenerational transfers, and common pool problems. Fiscal rules aim to eliminate the problem of time inconsistency of public finances and minimize debt accumulation by setting debt limits. Despite the theoretical relevance of fiscal rules and institutions to the proper management of fiscal processes in different countries, the evidence indicates mixed results regarding the effectiveness of this type of mechanism for fiscal performance. To understand the effect that fiscal rules have on public debt, this paper studies the effect of different types of rules on debt behavior and their differential effects with respect to the economic cycle. Using a dynamic panel, which enables us to control for endogeneity problems, and the use of a fiscal rule quality index (Schaechter et. al., 2012), this paper finds that fiscal rules only have a significant effect on the reduction of public debt during the positive side of the economic cycle if adequate institutional arrangements accompany them. Furthermore, only some types of fiscal rules (expenditure rules) show a significant effect during the negative part of the cycle. These results have relevant policy implications, as they underscore the importance of (1) developing institutional arrangements that promote the proper functioning of fiscal rules and (2) considering economic cycle asymmetries in order to ensure the appropriate operation of fiscal rules and the fulfillment of policy objectives.
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Babuska, Ivo M., and Rodolfo Rodriguez. The Problem of the Selection of an A-Posteriori Error Indicator Based on Smoothening Techniques. Fort Belvoir, VA: Defense Technical Information Center, August 1991. http://dx.doi.org/10.21236/ada253401.

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