Radial Basis Function Networks 2
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Radial Basis Function Networks 2
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Author : Robert J. Howlett
language : en
Publisher: Physica
Release Date : 2013-03-19
Radial Basis Function Networks 2 written by Robert J. Howlett and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-19 with Computers categories.
The Radial Basis Function (RBF) network has gained in popularity in recent years. This is due to its desirable properties in classification and functional approximation applications, accompanied by training that is more rapid than that of many other neural-network techniques. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of applications areas, for example, robotics, biomedical engineering, and the financial sector. The two-title series Theory and Applications of Radial Basis Function Networks provides a comprehensive survey of recent RBF network research. This volume, New Advances in Design, contains a wide range of applications in the laboratory and case-studies describing current use. The sister volume to this one, Recent Developments in Theory and Applications, covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms. The combination of the two volumes will prove extremely useful to practitioners in the field, engineers, researchers, students and technically accomplished managers.
Radial Basis Function Networks 2
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Author : Springer
language : en
Publisher:
Release Date : 2014-01-15
Radial Basis Function Networks 2 written by Springer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Radial Basis Function Networks 2
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Author : Robert J. Howlett
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-03-27
Radial Basis Function Networks 2 written by Robert J. Howlett and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-03-27 with Computers categories.
The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of application areas, for example, robotics, biomedical engineering, and the financial sector. The two volumes provide a comprehensive survey of the latest developments in this area. Volume 2 contains a wide range of applications in the laboratory and case studies describing current industrial use. Both volumes will prove extremely useful to practitioners in the field, engineers, reserachers, students and technically accomplished managers.
Radial Basis Function Networks 2
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Author : Robert J. Howlett
language : en
Publisher: Physica
Release Date : 2001-03-27
Radial Basis Function Networks 2 written by Robert J. Howlett and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-03-27 with Computers categories.
The Radial Basis Function (RBF) network has gained in popularity in recent years. This is due to its desirable properties in classification and functional approximation applications, accompanied by training that is more rapid than that of many other neural-network techniques. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of applications areas, for example, robotics, biomedical engineering, and the financial sector. The two-title series Theory and Applications of Radial Basis Function Networks provides a comprehensive survey of recent RBF network research. This volume, New Advances in Design, contains a wide range of applications in the laboratory and case-studies describing current use. The sister volume to this one, Recent Developments in Theory and Applications, covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms. The combination of the two volumes will prove extremely useful to practitioners in the field, engineers, researchers, students and technically accomplished managers.
Radial Basis Networks
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2023-06-26
Radial Basis Networks written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-26 with Computers categories.
What Is Radial Basis Networks A radial basis function network is a type of artificial neural network that is used in the field of mathematical modeling. This type of network employs radial basis functions as its activation functions. The output of the network is a linear combination of the neuron parameters and the radial basis functions of the inputs to the network. Radial basis function networks have a wide range of applications, some of which include the approximation of functions, the prediction of time series, the classification of data, and the control of systems. In their study from 1988, Broomhead and Lowe, who were both researchers at the Royal Signals and Radar Establishment, were the ones who initially formulated the ideas. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Radial basis function network Chapter 2: Gradient Chapter 3: Radial basis function Chapter 4: Radial basis function kernel Chapter 5: Functional derivative Chapter 6: Jacobian matrix and determinant Chapter 7: Laplace's equation Chapter 8: Laplace operator Chapter 9: Multiple integral Chapter 10: Polyharmonic spline (II) Answering the public top questions about radial basis networks. (III) Real world examples for the usage of radial basis networks in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of radial basis networks. What Is Artificial Intelligence Series The Artificial Intelligence eBook series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The Artificial Intelligence eBook series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.
Radial Basis Function Rbf Neural Network Control For Mechanical Systems
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Author : Jinkun Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-26
Radial Basis Function Rbf Neural Network Control For Mechanical Systems written by Jinkun Liu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-26 with Technology & Engineering categories.
Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design. This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronautics.
Fully Tuned Radial Basis Function Neural Networks For Flight Control
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Author : N. Sundararajan
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Fully Tuned Radial Basis Function Neural Networks For Flight Control written by N. Sundararajan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Science categories.
Fully Tuned Radial Basis Function Neural Networks for Flight Control presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications. A Lyapunov synthesis approach is used to derive the tuning rules for the RBF controller parameters in order to guarantee the stability of the closed loop system. Unlike previous methods that tune only the weights of the RBF network, this book presents the derivation of the tuning law for tuning the centers, widths, and weights of the RBF network, and compares the results with existing algorithms. It also includes a detailed review of system identification, including indirect and direct adaptive control of nonlinear systems using neural networks. Fully Tuned Radial Basis Function Neural Networks for Flight Control is an excellent resource for professionals using neural adaptive controllers for flight control applications.
Self Organizing Neural Networks
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Author : Udo Seiffert
language : en
Publisher: Physica
Release Date : 2013-11-11
Self Organizing Neural Networks written by Udo Seiffert and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Computers categories.
The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. Introduced by Teuvo Kohonen in the 1980s, SOMs have been developed as a very powerful method for visualization and unsupervised classification tasks by an active and innovative community of interna tional researchers. A number of extensions and modifications have been developed during the last two decades. The reason is surely not that the original algorithm was imperfect or inad equate. It is rather the universal applicability and easy handling of the SOM. Com pared to many other network paradigms, only a few parameters need to be arranged and thus also for a beginner the network leads to useful and reliable results. Never theless there is scope for improvements and sophisticated new developments as this book impressively demonstrates. The number of published applications utilizing the SOM appears to be unending. As the title of this book indicates, the reader will benefit from some of the latest the oretical developments and will become acquainted with a number of challenging real-world applications. Our aim in producing this book has been to provide an up to-date treatment of the field of self-organizing neural networks, which will be ac cessible to researchers, practitioners and graduated students from diverse disciplines in academics and industry. We are very grateful to the father of the SOMs, Professor Teuvo Kohonen for sup porting this book and contributing the first chapter.
Radial Basis Function Networks 1
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Author : Robert J.Howlett
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-03-27
Radial Basis Function Networks 1 written by Robert J.Howlett and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-03-27 with Computers categories.
The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of application areas, for example, robotics, biomedical engineering, and the financial sector. The two volumes provide a comprehensive survey of the latest developments in this area. Volume 1 covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms, for example RBF learning using genetic algorithms. Both volumes will prove extremely useful to practitioners in the field, engineers, researchers and technically accomplished managers.
Neural Networks And Soft Computing
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Author : Leszek Rutkowski
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-20
Neural Networks And Soft Computing written by Leszek Rutkowski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-20 with Computers categories.
This volume presents new trends and developments in soft computing techniques. Topics include: neural networks, fuzzy systems, evolutionary computation, knowledge discovery, rough sets, and hybrid methods. It also covers various applications of soft computing techniques in economics, mechanics, medicine, automatics and image processing. The book contains contributions from internationally recognized scientists, such as Zadeh, Bubnicki, Pawlak, Amari, Batyrshin, Hirota, Koczy, Kosinski, Novák, S.-Y. Lee, Pedrycz, Raudys, Setiono, Sincak, Strumillo, Takagi, Usui, Wilamowski and Zurada. An excellent overview of soft computing methods and their applications.