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Books on the topic 'Stationary problems'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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1

Knight, Philip Anthony. Error analysis of stationary iteration and associated problems. Manchester: University of Manchester, 1993.

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2

Tassignon, H. Solutions to non-stationary problems in wavelet space. Leicester: SERCentre, De Montfort University, 1997.

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3

Tassignon, Hugo. Solutions to non-stationary problems in wavelet space. Leicester: De Montfort University, 1997.

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4

Mahler, Harry. Stationary engineer, high pressure plant tender, high pressure boiler operating engineer. 6th ed. New York: Arco Pub., 1985.

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5

Marti, Kurt. Computation of descent directions and stationary (efficient) points in stochastic optimization problems having discrete distributions. Neubiberg: Universität der Bundeswehr München, 1986.

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6

Zulehner, Walter. Numerische Mathematik: Stationa re Probleme. Basel: Birkha user, 2008.

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7

Verband Katholischer Einrichtungen der Heim- und Heilpädagogik., ed. Stationäre Erziehungshilfe für Mädchen. Freiburg im Breisgau: Lambertus, 1990.

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8

Stocker, Jennifer Rachel. The study of two problems in fluid mechanics using asymptotic and numerical methods: Part 1 Stationary perturbations of Couette-Poiseuille flow, the flow development in long cavities and channels : part 2 Unsteady flow past a circular cylinder in a rotating frame. Manchester: University of Manchester, 1995.

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9

Babeshko, Lyudmila, and Irina Orlova. Econometrics and econometric modeling in Excel and R. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079837.

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The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluation, analysis, and practical implementation of Box — Jenkins stationary time series models, as well as multidimensional time series models: vector autoregressive models and vector error correction models. It includes basic econometric models for panel data that have been widely used in recent decades, as well as formal tests for selecting models based on their hierarchical structure. Each section provides examples of evaluating, analyzing, and testing models in the R software environment. Meets the requirements of the Federal state educational standards of higher education of the latest generation. It is addressed to master's students studying in the Field of Economics, the curriculum of which includes the disciplines Econometrics (advanced course)", "Econometric modeling", "Econometric research", and graduate students."

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10

Non-Stationary Dynamical Problems in Astronomy. Nova Science Publishers, 2002.

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11

Komech, Alexander, and Anatoli Merzon. Stationary Diffraction by Wedges: Method of Automorphic Functions on Complex Characteristics. Springer, 2019.

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12

Avshalumov, Alexander Shamailovich. Theory of the Stationary Self-Consistent Universe. Publishing House Triumph, 2021. http://dx.doi.org/10.32986/978-5-94472-045-0-2021-3-92.

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Since the creation of GR and subsequent works in cosmology, the question of the curvature of space in the Universe is considered one of the most important and debated to this day. This is evident, because the curvature of space depends whether the Universe expands, contracts or is static. These discussions allowed the author to propose a paradoxical idea: simultaneous existence in the Universe of three interconnected space-times (positive, negative and zero curvature) and on this basis, to develop a theory in which each space-time plays its own role and develops in a strict accordance with its sign of curvature. The three space-time model of the structure of the Universe, proposed by the author, allows to solve many fundamental problems of modern cosmology and theoretical physics and creates the basis for building a unified physical theory (including one that unites GR and quantum physics).

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13

Methodology for simulation of unsteady flows to determine the time-dependent interference between stationary and moving boundaries: [abstract. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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14

Brodsky, Boris. Change-Point Analysis in Nonstationary Stochastic Models. Taylor & Francis Group, 2016.

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15

Brodsky, Boris. Change-Point Analysis in Nonstationary Stochastic Models. Taylor & Francis Group, 2016.

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16

Change-Point Analysis in Nonstationary Stochastic Models. Taylor & Francis Group, 2016.

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17

Brodsky, Boris. Change-Point Analysis in Nonstationary Stochastic Models. Taylor & Francis Group, 2017.

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18

Brodsky, Boris. Change-Point Analysis in Nonstationary Stochastic Models. CRC Press LLC, 2022.

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19

Mann, Peter. The Stationary Action Principle. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198822370.003.0007.

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This crucial chapter focuses on the stationary action principle. It introduces Lagrangian mechanics, using first-order variational calculus to derive the Euler–Lagrange equation, and the inverse problem is described. The chapter then considers the Ostrogradsky equation and discusses the properties of the extrema using the second-order variation to the action. It then discusses the difference between action functions (of Dirichlet boundary conditions) and action functionals of the extremal path. The different types of boundary conditions (Dirichlet vs Neumann) are elucidated. Topics discussed include Hessian conditions, Douglas’s theorem, the Jacobi last multiplier, Helmholtz conditions, Noether-type variation and Frenet–Serret frames, as well as concepts such as on shell and off shell. Actions of non-continuous extremals are examined using Weierstrass–Erdmann corner conditions, and the action principle is written in the most general form as the Hamilton–Suslov principle. Important applications of the Euler–Lagrange formulation are highlighted, including protein folding.

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20

Limebeer, D. J. N., and Matteo Massaro. Dynamics and Optimal Control of Road Vehicles. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198825715.001.0001.

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The broad aim of this book is to provide a comprehensive coverage of the modelling and optimal control of both two‐ and four‐wheeled road vehicles. The first focus of this book is a review of classical mechanics and its use in building vehicle and tyre dynamic models. The second is nonlinear optimal control, which is used to solve a range of minimum‐time, minimum‐fuel, and track curvature reconstruction problems. As is known classically, all thismaterial is bound together by the calculus of variations and stationary principles. The treatment of this material is supplemented with a large number of examples that highlight obscurities and subtleties in the theory. A particular strength of the book is its unified treatment of tyre, car, and motorcycle dynamics and the application of nonlinear optimal control to vehicle‐related problems within a single text. These topics are usually treated independently, and can only be found in disparate texts and journal articles. It is our contention that presentday vehicle dynamicists should be familiar with all of these topic areas. The aim in writing this book is to provide a comprehensive and yet accessible text that emphasizes particularly the theoretical aspects of vehicular modelling and control.

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21

Ferraty, Frédéric, and Yves Romain, eds. The Oxford Handbook of Functional Data Analysis. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.001.0001.

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This handbook presents the state-of-the-art of the statistics dealing with functional data analysis. With contributions from international experts in the field, it discusses a wide range of the most important statistical topics (classification, inference, factor-based analysis, regression modeling, resampling methods, time series, random processes) while also taking into account practical, methodological, and theoretical aspects of the problems. The book is organised into three sections. Part I deals with regression modeling and covers various statistical methods for functional data such as linear/nonparametric functional regression, varying coefficient models, and linear/nonparametric functional processes (i.e. functional time series). Part II considers related benchmark methods/tools for functional data analysis, including curve registration methods for preprocessing functional data, functional principal component analysis, and resampling/bootstrap methods. Finally, Part III examines some of the fundamental mathematical aspects of the infinite-dimensional setting, with a focus on the stochastic background and operatorial statistics: vector-valued function integration, spectral and random measures linked to stationary processes, operator geometry, vector integration and stochastic integration in Banach spaces, and operatorial statistics linked to quantum statistics.

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22

Dym, H., and H. P. McKean. Gaussian Processes, Function Theory, and the Inverse Spectral Problem. Dover Publications, 2008.

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23

Bauphysikalische Temperaturberechnungen in FORTRAN: Band 1 Zwei- bzw. dreidimensionale stationäre Probleme des Wärmeschutzes. Wiesbaden: Vieweg+Teubner Verlag, 1985.

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24

Petersson, Magnus. Denmark and Norway. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198790501.003.0021.

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Denmark and Norway joined NATO in 1949. Since then, their goal has been to be a loyal alliance member. After the cold war, the two countries e transformed their defence forces into small, capabilities-based semi-professional and highly mobile units suitable for coalition warfare far away from their territories. They have participated in all major US- and NATO-led operations since 1991. The defence transformation since the end of the cold war has been more far-reaching in Denmark than in Norway. Norway kept the focus on its territory during the whole period, and saved important elements of its territorial defence, while Denmark shut down whole services, such as submarines and stationary ground-to-air defence, which in some ways became a problem after the Ukraine crisis started in 2014, when the defence of the territory again came more into focus.

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