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Stable Adaptive Neural Network Control, S.S. Ge; C.C. Hang; T.H. Lee; Tao Zhang


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Автор: S.S. Ge; C.C. Hang; T.H. Lee; Tao Zhang
Название:  Stable Adaptive Neural Network Control
ISBN: 9781441949325
Издательство: Springer
Классификация:


ISBN-10: 1441949321
Обложка/Формат: Paperback
Страницы: 282
Вес: 0.42 кг.
Дата издания: 07.12.2010
Серия: The International Series on Asian Studies in Computer and Information Science
Язык: English
Размер: 234 x 156 x 16
Основная тема: Physics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Recent years have seen a rapid development of neural network control tech- niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec- tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications.


Stable Parametric Programming

Автор: S. Zlobec
Название: Stable Parametric Programming
ISBN: 1461348854 ISBN-13(EAN): 9781461348856
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book is a study of these notions and their relationship in linear and convex parametric programming models. Then new results in convex programming, using LFS functions, for single-objective, multi-objective, differentiable and non-smooth programs are introduced.

Introduction to Structurally Stable Systems of Differential Equations

Автор: S.Y. Pilyugin
Название: Introduction to Structurally Stable Systems of Differential Equations
ISBN: 303489712X ISBN-13(EAN): 9783034897129
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book is based on a one year course of lectures on structural sta- bility of differential equations which the author has given for the past several years at the Department of Mathematics and Mechanics at the University of Leningrad.

Dynamics of quasi-stable dissipative systems

Автор: Chueshov, Igor
Название: Dynamics of quasi-stable dissipative systems
ISBN: 3319229028 ISBN-13(EAN): 9783319229027
Издательство: Springer
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Цена: 8384.00 р.
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Описание: Dynamics of Quasi-Stable Dissipative Systems

Adaptive control

Автор: Landau, Ioan Dore Lozano, Rogelio M`saad, Mohammed
Название: Adaptive control
ISBN: 0857296639 ISBN-13(EAN): 9780857296634
Издательство: Springer
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Цена: 22359.00 р.
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Описание: Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the application of the ideas presented. The second edition is thoroughly revised to throw light on recent developments in theory and applications with new chapters on: multimodel adaptive control with switching, direct and indirect adaptive regulation and adaptive feedforward disturbance compensation. Many algorithms are newly presented in MATLAB® m-file format to facilitate their employment in real systems. Classroom-tested slides for instructors to use in teaching this material are also now provided. All of this supplementary electronic material can be downloaded from fill in URL. The core material is also up-dated and re-edited to keep its perspective in line with modern ideas and more closely to associate algorithms with their applications giving the reader a solid grounding in: synthesis and analysis of parameter adaptation algorithms, recursive plant model identification in open and closed loop, robust digital control for adaptive control; • robust parameter adaptation algorithms, practical considerations and applications, including flexible transmission systems, active vibration control and broadband disturbance rejection and a supplementary introduction on hot dip galvanizing and a phosphate drying furnace. Control researchers and applied mathematicians will find Adaptive Control of significant and enduring interest and its use of example and application will appeal to practitioners working with unknown- and variable-parameter plant. Praise for the first edition: …well written, interesting and easy to follow, so that it constitutes a valuable addition to the monographies in adaptive control for discrete-time linear systems… suitable (at least in part) for use in graduate courses in adaptive control.

Stable Convergence and Stable Limit Theorems

Автор: Hдusler Erich
Название: Stable Convergence and Stable Limit Theorems
ISBN: 3319183281 ISBN-13(EAN): 9783319183282
Издательство: Springer
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Цена: 11878.00 р.
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Описание: The authors present a concise but complete exposition of the mathematical theory of stable convergence and give various applications in different areas of probability theory and mathematical statistics to illustrate the usefulness of this concept.

Potential Analysis of Stable Processes and its Extensions

Автор: Piotr Graczyk; Krzysztof Bogdan; Tomasz Byczkowski
Название: Potential Analysis of Stable Processes and its Extensions
ISBN: 3642021409 ISBN-13(EAN): 9783642021404
Издательство: Springer
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Цена: 6288.00 р.
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Описание: Deals with the potential theory of stable stochastic processes. This book also deals with related topics, such as the subordinate Brownian motions and Feynman-Kac semigroups generated by certain Schroedinger operators. It focuses on classes of stable and related processes that contain the Brownian motion as a special case.

Stable Parametric Programming

Автор: S. Zlobec
Название: Stable Parametric Programming
ISBN: 0792371399 ISBN-13(EAN): 9780792371397
Издательство: Springer
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Цена: 19564.00 р.
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Описание: Optimality and stability are two important notions in applied mathematics. This book is a study of these notions and their relationship in linear and convex parametric programming models. Written in an analytic spirit, it begins with a survey of basic optimality conditions in nonlinear programming.

Stable Non-Gaussian Self-Similar Processes with Stationary Increments

Автор: Vladas Pipiras; Murad S. Taqqu
Название: Stable Non-Gaussian Self-Similar Processes with Stationary Increments
ISBN: 3319623303 ISBN-13(EAN): 9783319623306
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book provides a self-contained presentation on the structure of a large class of stable processes, known as self-similar mixed moving averages. The first sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed moving averages and self-similarity.

Discretization Methods for Stable Initial Value Problems

Автор: E. Gekeler
Название: Discretization Methods for Stable Initial Value Problems
ISBN: 3540128808 ISBN-13(EAN): 9783540128809
Издательство: Springer
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Цена: 6288.00 р.
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Stable Perturbations Of Operators And Related Topics

Автор: Xue Yifeng
Название: Stable Perturbations Of Operators And Related Topics
ISBN: 9814383597 ISBN-13(EAN): 9789814383592
Издательство: World Scientific Publishing
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Цена: 15048.00 р.
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Описание: A collection of articles that covers topics that range from Markov processes, backward stochastic differential equations, stochastic partial differential equations, stochastic control, potential theory, functional inequalities, optimal stopping, portfolio selection, to risk measure and risk theory.

Stable and Efficient Cubature-based Filtering in Dynamical Systems

Автор: Dominik Ballreich
Название: Stable and Efficient Cubature-based Filtering in Dynamical Systems
ISBN: 3319621297 ISBN-13(EAN): 9783319621296
Издательство: Springer
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Цена: 11878.00 р.
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Описание: The book addresses the problem of calculation of d-dimensional integrals (conditional expectations) in filter problems. It develops new methods of deterministic numerical integration, which can be used to speed up and stabilize filter algorithms.

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

Автор: Jinkun Liu
Название: Radial Basis Function (RBF) Neural Network Control for Mechanical Systems
ISBN: 364243455X ISBN-13(EAN): 9783642434556
Издательство: Springer
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Цена: 20896.00 р.
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Описание: This book introduces concrete design methods and MATLAB simulations of stable adaptive Radial Basis Function (RBF) neural control strategies. It presents a broad range of implementable neural network control design methods for mechanical systems.


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