Graph Theory and Decomposition, Kottarathil, Jomon ; Naduvath, Sudev ; Kureethara,
Автор: Kutz, J. Nathan Brunton, Steven L. Brunton, Bingni W. Proctor, Joshua L. Название: Dynamic mode decomposition ISBN: 1611974496 ISBN-13(EAN): 9781611974492 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 9593.00 р. Наличие на складе: Нет в наличии.
Описание: Data-driven dynamical systems is a burgeoning field - it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning.Dynamic Mode Decomposition is the first book to address the DMD algorithm, it:Presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development.Blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses.Highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences.Provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.
Автор: Balk Название: Productivity ISBN: 3030754502 ISBN-13(EAN): 9783030754501 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book develops the theory of productivity measurement using the empirical index number approach. The final chapter is devoted to the decomposition of productivity change into the contributions of efficiency change, technological change, scale effects, and input or output mix effects.
Автор: Dickopf Thomas, Gander Martin J., Halpern Laurence Название: Domain Decomposition Methods in Science and Engineering XXII ISBN: 3319792601 ISBN-13(EAN): 9783319792606 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: These are the proceedings of the 22nd International Conference on Domain Decomposition Methods, which was held in Lugano, Switzerland.
Автор: Andrea Toselli; Olof Widlund Название: Domain Decomposition Methods - Algorithms and Theory ISBN: 3642058485 ISBN-13(EAN): 9783642058486 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a comprehensive presentation of some of the most successful and popular domain decomposition preconditioners for finite and spectral element approximations of partial differential equations. It covers in detail important methods such as FETI and balancing Neumann-Neumann methods and algorithms for spectral element methods.
Автор: Bob F. Caviness; Jeremy R. Johnson Название: Quantifier Elimination and Cylindrical Algebraic Decomposition ISBN: 3211827943 ISBN-13(EAN): 9783211827949 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A collection of major papers on CAD and QE and on the related area of algorthmic aspects of real geometry. The work contains papers from a symposium held in Linz in 1993, reprints of seminal papers from the area, outlining Tarski`s paper, as well as a survey outlining the developments in CAD.
Описание: This valuable reference on projectors, generalized inverses, and SVD covers concepts numerous cutting-edge concepts and provides systematic and in-depth accounts of these ideas from the viewpoint of linear transformations of finite dimensional vector spaces.
Автор: Yunqing Huang; Ralf Kornhuber; Olof Widlund; Jinch Название: Domain Decomposition Methods in Science and Engineering XIX ISBN: 3642265693 ISBN-13(EAN): 9783642265693 Издательство: Springer Рейтинг: Цена: 24456.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: These are the proceedings of the 19th international conference on domain decomposition methods in science and engineering.
Автор: M. Pollack; Qiang Yang Название: Intelligent Planning ISBN: 3642644775 ISBN-13(EAN): 9783642644771 Издательство: Springer Рейтинг: Цена: 11173.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Indeed, the basic description of a plan generation algorithm has remained constant for nearly three decades: given a desciption of an initial state I, a goal state G, and a set of action types, find a sequence S of instantiated actions such that when S is executed instate I, G is guaranteed as a result.
Автор: M. Vidyasagar Название: Input-Output Analysis of Large-Scale Interconnected Systems ISBN: 3540105018 ISBN-13(EAN): 9783540105015 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Dmytro Iatsenko Название: Nonlinear Mode Decomposition ISBN: 331938712X ISBN-13(EAN): 9783319387123 Издательство: Springer Рейтинг: Цена: 13059.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This work introduces a new method for analysing measured signals: nonlinear mode decomposition, or NMD. Scientists often need to be able to analyse time series data that include a complex combination of oscillatory modes of differing origin, usually contaminated by random fluctuations or noise.
Автор: Thomas Carraro; Michael Geiger; Stefan K?rkel; Rol Название: Multiple Shooting and Time Domain Decomposition Methods ISBN: 3319233203 ISBN-13(EAN): 9783319233208 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
T. Akman et al: Space-Time Discontinuous Galerkin Methods for Optimal Control Problems Governed by Time Dependent Diffusion-Convection-Reaction Equations.- Th. Carraro et al: Direct and Indirect Multiple Shooting for Parabolic Optimal Control Problems.- M.J. Gander: 50 Years of Time Parallel Time Integration.- S. Grцtschel et al: Reducing Memory Requirements in Scientific Computing and Optimal Control.- Y. Hasegawa: Optimal Control of Heat and Fluid Flow for Efficient Energy Utilization.- D. Janka et al: Direct Multiple Shooting for Optimum Experimental Design.- D. Kaschek et al: A Unified Approach to Integration and Optimization of Parametric Ordinary Differential Equations.- R. Kircheis et al: Parameter Estimation for PDAE Constrained Models Using a Reduced Approach.- M. Klinger: A Variational Approach for Physically Based Image Interpolation Across Boundaries.- C. Kreutz et al: Statistics for Model Calibration.- A. Potschka: Direct Multiple Shooting for Parabolic PDE Constrained Optimization.- R. Quirynen et al: Multiple Shooting in a Microsecond.- Th. Richter et al: Time Discretizations of Fluid-Structure Interactions.- St. Ulbrich: Preconditioners Based on 'Parareal' Time-Domain Decomposition for Time-Dependent PDE-Constrained Optimization.- E. Kostina et al: Direct Multiple Shooting for Optimization Problems in ODE Models.- M. Schlick: Parareal Time-Stepping for Limit-Cycle Computation of the Incompressible Navier-Stokes Equations with Uncertain Periodic Dynamics.
Описание: This book provides an elementary analytically inclined journey to a fundamental result of linear algebra: the Singular Value Decomposition (SVD). SVD is a workhorse in many applications of linear algebra to data science. Four important applications relevant to data science are considered throughout the book: determining the subspace that ""best'' approximates a given set (dimension reduction of a data set); finding the ""best'' lower rank approximation of a given matrix (compression and general approximation problems); the Moore-Penrose pseudo-inverse (relevant to solving least squares problems); and the orthogonal Procrustes problem (finding the orthogonal transformation that most closely transforms a given collection to a given configuration), as well as its orientation-preserving version.The point of view throughout is analytic. Readers are assumed to have had a rigorous introduction to sequences and continuity. These are generalized and applied to linear algebraic ideas. Along the way to the SVD, several important results relevant to a wide variety of fields (including random matrices and spectral graph theory) are explored: the Spectral Theorem; minimax characterizations of eigenvalues; and eigenvalue inequalities. By combining analytic and linear algebraic ideas, readers see seemingly disparate areas interacting in beautiful and applicable ways.
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