Описание: This brief book presents the strong fractional analysis of Banach space valued functions of a real domain. The book`s results are abstract in nature: analytic inequalities, Korovkin approximation of functions and neural network approximation.
Автор: George A. Anastassiou Название: Intelligent Comparisons: Analytic Inequalities ISBN: 331937060X ISBN-13(EAN): 9783319370606 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The chapters are self-contained and can be read independently, they include an extensive list of references per chapter.The book`s results are expected to find applications in many areas of applied and pure mathematics, especially in ordinary and partial differential equations and fractional differential equations.
Описание: This book book explores the ways that elaborate flux functions can be constructed, mainly in a one-dimensional context for hyperbolic systems admitting shock-type solutions and also for kinetic equations in the discrete-ordinate approximation.
Описание: It also explores approximations under convexity and a new trend in approximation theory - approximation by sublinear operators with applications to max-product operators, which are nonlinear and rational providing very fast and flexible approximations.
Описание: This compact book focuses on self-adjoint operators` well-known named inequalities and Korovkin approximation theory, both in a Hilbert space environment. As such, the book offers a valuable resource for researchers and graduate students alike, as well as a key addition to all science and engineering libraries.
This brief book presents the strong fractional analysis of Banach space valued functions of a real domain. The book’s results are abstract in nature: analytic inequalities, Korovkin approximation of functions and neural network approximation. The chapters are self-contained and can be read independently.
This concise book is suitable for use in related graduate classes and many research projects. An extensive list of references is provided for each chapter. The book’s results are relevant for many areas of pure and applied mathematics. As such, it offers a unique resource for researchers, and a valuable addition to all science and engineering libraries.
Описание: This book focuses on computational and fractional analysis, two areas that are very important in their own right, and which are used in a broad variety of real-world applications. We also cover the conformable fractional approximation of Csiszar`s well-known f-divergence, and present conformable fractional self-adjoint operator inequalities.
Автор: George A. Anastassiou Название: Intelligent Comparisons: Analytic Inequalities ISBN: 331921120X ISBN-13(EAN): 9783319211206 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The chapters are self-contained and can be read independently, they include an extensive list of references per chapter.The book`s results are expected to find applications in many areas of applied and pure mathematics, especially in ordinary and partial differential equations and fractional differential equations.
Автор: Riccardo Zoppoli; Marcello Sanguineti; Giorgio Gne Название: Neural Approximations for Optimal Control and Decision ISBN: 3030296911 ISBN-13(EAN): 9783030296919 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Поставка под заказ.
Описание: Neural Approximations for Optimal Control and Decision provides a comprehensive methodology for the approximate solution of functional optimization problems using neural networks and other nonlinear approximators where the use of traditional optimal control tools is prohibited by complicating factors like non-Gaussian noise, strong nonlinearities, large dimension of state and control vectors, etc.Features of the text include:• a general functional optimization framework;• thorough illustration of recent theoretical insights into the approximate solutions of complex functional optimization problems;• comparison of classical and neural-network based methods of approximate solution;• bounds to the errors of approximate solutions;• solution algorithms for optimal control and decision in deterministic or stochastic environments with perfect or imperfect state measurements over a finite or infinite time horizon and with one decision maker or several;• applications of current interest: routing in communications networks, traffic control, water resource management, etc.; and• numerous, numerically detailed examples.The authors’ diverse backgrounds in systems and control theory, approximation theory, machine learning, and operations research lend the book a range of expertise and subject matter appealing to academics and graduate students in any of those disciplines together with computer science and other areas of engineering.
Описание: Preview of Predictor Feedback and Delay Compensation.- Part I: Linear Systems Under Predictor Feedback.- Linear Systems with State Measurement.- Linear Systems with Output Measurement.- Part II: Nonlinear Systems Under Predictor Feedback.- Nonlinear Systems with State Measurement.- Nonlinear Systems with Output Measurement.- Application to the Chemostat.- Part III: Extensions of Predictor Feedback.- Systems Described by Integral Delay Equations.- Discrete-Time Systems.
Автор: Saldi, Naci. Название: Finite approximations in discrete-time stochastic control : ISBN: 3319790323 ISBN-13(EAN): 9783319790329 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems.
This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original models and the methods are general enough that researchers can build corresponding approximation results, typically with no additional assumptions.
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