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.
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 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.
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.
Описание: This book comes as a result of the research work developed in the framework of two large international projects: the European Science Foundation (ESF) supported program NATEMIS (Nonlinear Acoustic Techniques for Micro-Scale Damage Diagnostics) (of which Professor Delsanto was the European coordinator, 2000-2004) and a Los Alamos-based network headed by Dr. P.A. Johnson. The main topic of both programs and of this book is the description of the phenomenology, theory and applications of nonclassical Nonlinearity (NCNL). In fact NCNL techniques have been found in recent years to be extremely powerful (up to more than 1000 times with respect to the corresponding linear techniques) in a wide range of applications, including Elasticity, Material Characterization, Ultrasonics, Geophysics to Maintenance and Restoration of artifacts (paintings, stone buildings, etc.). The book is divided into three parts: Part I - defines and describes the concept of NCNL and its universality and reviews several fields to which it may apply; Part II - describes the phenomenology, theory, modelling and virtual experiments (simulations); Part III - discusses some of the most relevant experimental techniques and applications.
Автор: Albert Benveniste; S.S. Wilson; Michel Metivier; P Название: Adaptive Algorithms and Stochastic Approximations ISBN: 3642758967 ISBN-13(EAN): 9783642758966 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Adaptive systems are widely encountered in many applications ranging through adaptive filtering and more generally adaptive signal processing, systems identification and adaptive control, to pattern recognition and machine intelligence: adaptation is now recognised as keystone of "intelligence" within computerised systems.
Автор: Maria Tomas-Rodriguez; Stephen P. Banks Название: Linear, Time-varying Approximations to Nonlinear Dynamical Systems ISBN: 184996100X ISBN-13(EAN): 9781849961004 Издательство: Springer Рейтинг: Цена: 25853.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A new technique for analysing and controlling nonlinear systems is introduced in this book. Although the methods outlined are novel, they can be simply implemented using pre-existing and widely known classical control ideas.
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.
Автор: Naci Saldi; Tam?s Linder; Serdar Y?ksel Название: Finite Approximations in Discrete-Time Stochastic Control ISBN: 3030077101 ISBN-13(EAN): 9783030077105 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.
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: 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.
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