Автор: Cesare Alippi; Marios M. Polycarpou; Christos Pana Название: Artificial Neural Networks – ICANN 2009 ISBN: 3642042732 ISBN-13(EAN): 9783642042737 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS).
Автор: Leonardo Franco; Jos? M. Jerez Название: Constructive Neural Networks ISBN: 3642045111 ISBN-13(EAN): 9783642045110 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constructive neural networks and other incremental learning algorithms are discussed in this volume as alternatives to methods for assessing adequate architectures. A valuable overview of the field is presented, in addition to useful applications.
Автор: James Kwok; Bao-Liang Lu; Liqing Zhang; Bao-Liang Название: Advances in Neural Networks -- ISNN 2010 ISBN: 3642132774 ISBN-13(EAN): 9783642132773 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the proceedings of the 7th International Symposium on Neural Networks, ISNN 2010, held in Shanghai, China, June 6-9, 2010. This title presents the papers that focus on topics such as Neurophysiological Foundation, Theory and Models, Learning and Inference, and Neurodynamics.
Автор: Johann M.Ph. Schumann; Yan Liu Название: Applications of Neural Networks in High Assurance Systems ISBN: 3642106897 ISBN-13(EAN): 9783642106897 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is the first book to directly address a key part of neural network technology: state-of-the-art methods used to pass the tough verification and validation standards required in many safety-critical applications.
Автор: Leonardo Franco; Jos? M. Jerez Название: Constructive Neural Networks ISBN: 3642261086 ISBN-13(EAN): 9783642261084 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constructive neural networks and other incremental learning algorithms are discussed in this volume as alternatives to methods for assessing adequate architectures. A valuable overview of the field is presented, in addition to useful applications.
Описание: This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc.
Автор: Jouke Annema Название: Feed-Forward Neural Networks ISBN: 1461359902 ISBN-13(EAN): 9781461359906 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation presents a novel method for the mathematical analysis of neural networks that learn according to the back-propagation algorithm.
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: Cesare Alippi; Marios M. Polycarpou; Christos Pana Название: Artificial Neural Networks – ICANN 2009 ISBN: 3642042767 ISBN-13(EAN): 9783642042768 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS).
Автор: James Kwok; Liqing Zhang; Bao-Liang Lu Название: Advances in Neural Networks -- ISNN 2010 ISBN: 3642133177 ISBN-13(EAN): 9783642133176 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the proceedings of the 7th International Symposium on Neural Networks, ISNN 2010, held in Shanghai, China, June 6-9, 2010. This title presents the papers that focus on topics such as SVM and Kernel Methods, Vision and Image, Data Mining and Text Analysis, BCI and Brain Imaging and its applications.
Автор: Erdal Kayacan Название: Fuzzy Neural Networks for Real Time Control Applications ISBN: 0128026871 ISBN-13(EAN): 9780128026878 Издательство: Elsevier Science Рейтинг: Цена: 12294.00 р. Наличие на складе: Поставка под заказ.
Описание:
AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS
Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book
Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book.
A clear and an in-depth examination has been made of all the necessary mathematical foundations, type-1 and type-2 fuzzy neural network structures and their learning algorithms as well as their stability analysis.
You will find that each chapter is devoted to a different learning algorithm for the tuning of type-1 and type-2 fuzzy neural networks; some of which are:
- Gradient descent
- Levenberg-Marquardt
- Extended Kalman filter
In addition to the aforementioned conventional learning methods above, number of novel sliding mode control theory-based learning algorithms, which are simpler and have closed forms, and their stability analysis have been proposed. Furthermore, hybrid methods consisting of particle swarm optimization and sliding mode control theory-based algorithms have also been introduced.
The potential readers of this book are expected to be the undergraduate and graduate students, engineers, mathematicians and computer scientists. Not only can this book be used as a reference source for a scientist who is interested in fuzzy neural networks and their real-time implementations but also as a course book of fuzzy neural networks or artificial intelligence in master or doctorate university studies. We hope that this book will serve its main purpose successfully.
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