Intelligent Systems Ii Complete Approximation By Neural Network Operators

Author : George A. Anastassiou
Publisher : Springer
Page : 712 pages
File Size : 50,8 Mb
Release : 2015-06-23
Category : Technology & Engineering
ISBN : 9783319205052

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Intelligent Systems II: Complete Approximation by Neural Network Operators by George A. Anastassiou Pdf

This monograph is the continuation and completion of the monograph, “Intelligent Systems: Approximation by Artificial Neural Networks” written by the same author and published 2011 by Springer. The book you hold in hand presents the complete recent and original work of the author in approximation by neural networks. Chapters are written in a self-contained style and can be read independently. Advanced courses and seminars can be taught out of this brief book. All necessary background and motivations are given per chapter. A related list of references is given also per chapter. The book’s results are expected to find applications in many areas of applied mathematics, computer science and engineering. As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also for all science and engineering libraries.

Author : George A. Anastassiou
Publisher : Springer Science & Business Media
Page : 113 pages
File Size : 51,5 Mb
Release : 2011-06-02
Category : Technology & Engineering
ISBN : 9783642214318

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Intelligent Systems: Approximation by Artificial Neural Networks by George A. Anastassiou Pdf

This brief monograph is the first one to deal exclusively with the quantitative approximation by artificial neural networks to the identity-unit operator. Here we study with rates the approximation properties of the "right" sigmoidal and hyperbolic tangent artificial neural network positive linear operators. In particular we study the degree of approximation of these operators to the unit operator in the univariate and multivariate cases over bounded or unbounded domains. This is given via inequalities and with the use of modulus of continuity of the involved function or its higher order derivative. We examine the real and complex cases. For the convenience of the reader, the chapters of this book are written in a self-contained style. This treatise relies on author's last two years of related research work. Advanced courses and seminars can be taught out of this brief book. All necessary background and motivations are given per chapter. A related list of references is given also per chapter. The exposed results are expected to find applications in many areas of computer science and applied mathematics, such as neural networks, intelligent systems, complexity theory, learning theory, vision and approximation theory, etc. As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also for all science libraries.

Author : George A. Anastassiou
Publisher : Springer
Page : 224 pages
File Size : 45,8 Mb
Release : 2017-01-13
Category : Technology & Engineering
ISBN : 9783319514758

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Intelligent Comparisons II: Operator Inequalities and Approximations by George A. Anastassiou Pdf

This compact book focuses on self-adjoint operators’ well-known named inequalities and Korovkin approximation theory, both in a Hilbert space environment. It is the first book to study these aspects, and all chapters are self-contained and can be read independently. Further, each chapter includes an extensive list of references for further reading. The book’s results are expected to find applications in many areas of pure and applied mathematics. Given its concise format, it is especially suitable for use in related graduate classes and research projects. 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.

Author : George A. Anastassiou
Publisher : Springer Nature
Page : 429 pages
File Size : 41,8 Mb
Release : 2022-10-01
Category : Technology & Engineering
ISBN : 9783031164002

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Banach Space Valued Neural Network by George A. Anastassiou Pdf

This book is about the generalization and modernization of approximation by neural network operators. Functions under approximation and the neural networks are Banach space valued. These are induced by a great variety of activation functions deriving from the arctangent, algebraic, Gudermannian, and generalized symmetric sigmoid functions. Ordinary, fractional, fuzzy, and stochastic approximations are exhibited at the univariate, fractional, and multivariate levels. Iterated-sequential approximations are also covered. The book’s results are expected to find applications in the many areas of applied mathematics, computer science and engineering, especially in artificial intelligence and machine learning. Other possible applications can be in applied sciences like statistics, economics, etc. Therefore, this book is suitable for researchers, graduate students, practitioners, and seminars of the above disciplines, also to be in all science and engineering libraries.

Author : George A. Anastassiou
Publisher : Springer Nature
Page : 854 pages
File Size : 52,7 Mb
Release : 2023-09-29
Category : Technology & Engineering
ISBN : 9783031430213

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Parametrized, Deformed and General Neural Networks by George A. Anastassiou Pdf

In this book, we introduce the parametrized, deformed and general activation function of neural networks. The parametrized activation function kills much less neurons than the original one. The asymmetry of the brain is best expressed by deformed activation functions. Along with a great variety of activation functions, general activation functions are also engaged. Thus, in this book, all presented is original work by the author given at a very general level to cover a maximum number of different kinds of neural networks: giving ordinary, fractional, fuzzy and stochastic approximations. It presents here univariate, fractional and multivariate approximations. Iterated sequential multi-layer approximations are also studied. The functions under approximation and neural networks are Banach space valued.

Author : George A. Anastassiou
Publisher : Springer
Page : 347 pages
File Size : 48,8 Mb
Release : 2018-12-07
Category : Technology & Engineering
ISBN : 9783030042875

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Ordinary and Fractional Approximation by Non-additive Integrals: Choquet, Shilkret and Sugeno Integral Approximators by George A. Anastassiou Pdf

Ordinary and fractional approximations by non-additive integrals, especially by integral approximators of Choquet, Silkret and Sugeno types, are a new trend in approximation theory. These integrals are only subadditive and only the first two are positive linear, and they produce very fast and flexible approximations based on limited data. The author presents both the univariate and multivariate cases. The involved set functions are much weaker forms of the Lebesgue measure and they were conceived to fulfill the needs of economic theory and other applied sciences. The approaches presented here are original, and all chapters are self-contained and can be read independently. Moreover, the book’s findings are sure to find application in many areas of pure and applied mathematics, especially in approximation theory, numerical analysis and mathematical economics (both ordinary and fractional). Accordingly, it offers a unique resource for researchers, graduate students, and for coursework in the above-mentioned fields, and belongs in all science and engineering libraries.

Author : Jagdev Singh
Publisher : Springer Nature
Page : 365 pages
File Size : 42,8 Mb
Release : 2024-06-30
Category : Electronic
ISBN : 9783031563041

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Advances in Mathematical Modelling, Applied Analysis and Computation by Jagdev Singh Pdf

Author : George A. Anastassiou
Publisher : Springer
Page : 319 pages
File Size : 43,5 Mb
Release : 2017-09-02
Category : Technology & Engineering
ISBN : 9783319669366

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Intelligent Computations: Abstract Fractional Calculus, Inequalities, Approximations by George A. Anastassiou Pdf

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.

Author : Puyin Liu,Hong-Xing Li
Publisher : World Scientific
Page : 400 pages
File Size : 44,7 Mb
Release : 2004
Category : Computers
ISBN : 9812794212

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Fuzzy Neural Network Theory and Application by Puyin Liu,Hong-Xing Li Pdf

This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to help the reader grasp the underlying theory. This is a valuable reference for scientists and engineers working in mathematics, computer science, control or other fields related to information processing. It can also be used as a textbook for graduate courses in applied mathematics, computer science, automatic control and electrical engineering. Contents: Fuzzy Neural Networks for Storing and Classifying; Fuzzy Associative Memory OCo Feedback Networks; Regular Fuzzy Neural Networks; Polygonal Fuzzy Neural Networks; Approximation Analysis of Fuzzy Systems; Stochastic Fuzzy Systems and Approximations; Application of FNN to Image Restoration. Readership: Scientists, engineers and graduate students in applied mathematics, computer science, automatic control and information processing."

Author : James M. Keller,Derong Liu,David B. Fogel
Publisher : John Wiley & Sons
Page : 378 pages
File Size : 44,5 Mb
Release : 2016-07-13
Category : Technology & Engineering
ISBN : 9781119214366

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Fundamentals of Computational Intelligence by James M. Keller,Derong Liu,David B. Fogel Pdf

Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.

Author : Maureen Caudill,Charles T. Butler
Publisher : MIT Press
Page : 324 pages
File Size : 47,6 Mb
Release : 1990
Category : Computers
ISBN : 0262531135

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Naturally Intelligent Systems by Maureen Caudill,Charles T. Butler Pdf

Naturally Intelligent Systems offers a comprehensive introduction to neural networks.

Author : Butler,Caudill
Publisher : Unknown
Page : 128 pages
File Size : 42,7 Mb
Release : 1989
Category : Electronic
ISBN : 0805802134

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Naturally Intelligent Systems by Butler,Caudill Pdf

Author : Claudio Turchetti
Publisher : IOS Press
Page : 202 pages
File Size : 49,7 Mb
Release : 2004
Category : Neural networks (Computer science)
ISBN : 4274906264

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Stochastic Models of Neural Networks by Claudio Turchetti Pdf

Author : László T. Kóczy,Claudiu R. Pozna,Janusz Kacprzyk
Publisher : Springer
Page : 318 pages
File Size : 47,6 Mb
Release : 2014-01-11
Category : Technology & Engineering
ISBN : 9783319032061

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Issues and Challenges of Intelligent Systems and Computational Intelligence by László T. Kóczy,Claudiu R. Pozna,Janusz Kacprzyk Pdf

This carefully edited book contains contributions of prominent and active researchers and scholars in the broadly perceived area of intelligent systems. The book is unique both with respect to the width of coverage of tools and techniques, and to the variety of problems that could be solved by the tools and techniques presented. The editors have been able to gather a very good collection of relevant and original papers by prominent representatives of many areas, relevant both to the theory and practice of intelligent systems, artificial intelligence, computational intelligence, soft computing, and the like. The contributions have been divided into 7 parts presenting first more fundamental and theoretical contributions, and then applications in relevant areas.

Author : Robert J. Schalkoff
Publisher : Jones & Bartlett Learning
Page : 787 pages
File Size : 46,7 Mb
Release : 2011-08-24
Category : Computers
ISBN : 9780763780173

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Intelligent Systems by Robert J. Schalkoff Pdf

Artificial Intelligence has changed significantly in recent years and many new resources and approaches are now available to explore and implement this important technology. Intelligent Systems: Principles, Paradigms, and Pragmatics takes a modern, 21st-century approach to the concepts of Artificial Intelligence and includes the latest developments, developmental tools, programming, and approaches related to AI. The author is careful to make the important distinction between theory and practice, and focuses on a broad core of technologies, providing students with an accessible and comprehensive introduction to key AI topics.