Artificial Neural Networks for Modelling and Control of Non-Linear Systems, Johan A.K. Suykens; Joos P.L. Vandewalle; B.L. de
Автор: Sul Название: Control of Electric Machine Drive Systems ISBN: 0470590793 ISBN-13(EAN): 9780470590799 Издательство: Wiley Рейтинг: Цена: 20901.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Based on the author`s industry experience and collaborative works with other industries, Control of Electric Machine Drive System is packed with implemented, tested, and verified ideas that relate to everyday problems in the field.
Описание: The technology of neural networks has attracted much attention in recent years. Their ability to learn nonlinear relationships is widely appreciated and is utilized in many different types of applications; modelling of dynamic systems, signal processing, and control system design being some of the most common. The theory of neural computing has matured considerably over the last decade and many problems of neural network design, training and evaluation have been resolved. This book provides a comprehensive introduction to the most popular class of neural network, the multilayer perceptron, and shows how it can be used for system identification and control. It aims to provide the reader with a sufficient theoretical background to understand the characteristics of different methods, to be aware of the pit-falls and to make proper decisions in all situations. The subjects treated include: System identification: multilayer perceptrons; how to conduct informative experiments; model structure selection; training methods; model validation; pruning algorithms. Control: direct inverse, internal model, feedforward, optimal and predictive control; feedback linearization and instantaneous-linearization-based controllers. Case studies: prediction of sunspot activity; modelling of a hydraulic actuator; control of a pneumatic servomechanism; water-level control in a conical tank. The book is very application-oriented and gives detailed and pragmatic recommendations that guide the user through the plethora of methods suggested in the literature. Furthermore, it attempts to introduce sound working procedures that can lead to efficient neural network solutions. This will make the book invaluable to the practitioner and as a textbook in courses with a significant hands-on component.
Автор: Krzysztof J. Latawiec; Marian ?ukaniszyn; Rafa? St Название: Advances in Modelling and Control of Non-integer-Order Systems ISBN: 3319098993 ISBN-13(EAN): 9783319098999 Издательство: Springer Рейтинг: Цена: 28734.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents selected aspects of non-integer, or fractional order systems, whose analysis, synthesis and applications have increasingly become a real challenge for various research communities, ranging from science to engineering.
Автор: Petia Koprinkova-Hristova; Valeri Mladenov; Nikola Название: Artificial Neural Networks ISBN: 3319099027 ISBN-13(EAN): 9783319099026 Издательство: Springer Рейтинг: Цена: 34937.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.
Автор: Petia Koprinkova-Hristova; Valeri Mladenov; Nikola Название: Artificial Neural Networks ISBN: 3319349503 ISBN-13(EAN): 9783319349503 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.
Автор: Sied Mehdi Fakhraie; Kenneth C. Smith Название: VLSI — Compatible Implementations for Artificial Neural Networks ISBN: 1461378974 ISBN-13(EAN): 9781461378976 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces several state-of-the-art VLSI implementations of artificial neural networks (ANNs). The work of Professors Fakhraie and Smith, presented in this book, is a welcome addition to the state-of-the-art and will greatly benefit researchers and students working in this area.
Описание: How does a machine learn a new concept on the basis of examples? This second edition takes account of important new developments in the field. It also deals extensively with the theory of learning control systems, now comparably mature to learning of neural networks.
Автор: Jose G. Delgado-Frias; W.R. Moore Название: VLSI for Artificial Intelligence and Neural Networks ISBN: 1461366712 ISBN-13(EAN): 9781461366713 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is an edited selection of the papers presented at the International Workshop on VLSI for Artifidal Intelligence and Neural Networks which was held at the University of Oxford in September 1990.
Автор: Krzysztof J. Latawiec; Marian ?ukaniszyn; Rafa? St Название: Advances in Modelling and Control of Non-integer-Order Systems ISBN: 3319360477 ISBN-13(EAN): 9783319360478 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents selected aspects of non-integer, or fractional order systems, whose analysis, synthesis and applications have increasingly become a real challenge for various research communities, ranging from science to engineering.
Название: Vlsi for neural networks and artificial intelligence ISBN: 1489913335 ISBN-13(EAN): 9781489913333 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Neural network and artificial intelligence algorithrns and computing have increased not only in complexity but also in the number of applications. the areas are: analog circuits for neural networks, digital implementations of neural networks, neural networks on multiprocessor systems and applications, and VLSI machines for artificial intelligence.
Автор: Sied Mehdi Fakhraie; Kenneth C. Smith Название: VLSI — Compatible Implementations for Artificial Neural Networks ISBN: 0792398254 ISBN-13(EAN): 9780792398257 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduces an approach to biologically-inspired and VLSI-compatible definition, simulation, and implementation of artificial neural networks. This book develops a set of guidelines for general hardware implementation of artificial neural networks. It provides a geometrical interpretation of the behavior of different variants of these networks.
Автор: Mohamed I. Elmasry Название: VLSI Artificial Neural Networks Engineering ISBN: 0792394933 ISBN-13(EAN): 9780792394938 Издательство: Springer Рейтинг: Цена: 26122.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Offers an engineering approach to the design of VLSI Artificial Neural Networks (ANNs). This title presents the design of analog, digital and mixed analog/digital VLSI ANNs. It provides a design methodology and a CAD environment to highlight the tradeoff design factors. It includes system applications of ANNs to automatic speech recognition.
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