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Introduction to neural networks, Gurney, Kevin



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Автор: Gurney, Kevin
Название:  Introduction to neural networks
Перевод названия: Кевин Герни: Введение в нейронные сети
ISBN: 9781857285031
Издательство: Taylor&Francis
Классификация:
ISBN-10: 1857285034
Обложка/Формат: Paperback
Страницы: 248
Вес: 0.366 кг.
Дата издания: 05.08.1997
Язык: English
Иллюстрации: 135 illustrations
Размер: 23.29 x 15.57 x 1.47 cm
Читательская аудитория: Postgraduate, research & scholarly
Ссылка на Издательство: Link
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Поставляется из: Англии



Neural Networks for Pattern Recognition

Автор: Bishop, Christopher M.
Название: Neural Networks for Pattern Recognition
ISBN: 0198538642 ISBN-13(EAN): 9780198538646
Издательство: Oxford Academ
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Цена: 12293 р.
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Описание: Providing a comprehensive account of neural networks from a statistical perspective, this book emphasizes on pattern recognition, which represents the area of greatest applicability for neural networks in contemporary times.

Автор: Aminzadeh Fred, Sandham W., Leggett M.
Название: Geophysical Applications of Artificial Neural Networks and Fuzzy Logic
ISBN: 1402017294 ISBN-13(EAN): 9781402017292
Издательство: Springer
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Цена: 19304 р.
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Описание: This book is the first major text to encompass the wide diversity of geophysical applications of artificial neural networks (ANNs) and fuzzy logic (FZ). Each chapter, written by internationally-renowned experts in their field, represents a specific geophysical application, ranging from first-break picking and trace editing encountered in seismic exploration, through well-log lithology determination, to electromagnetic exploration and earthquake seismology. The book offers a well-balanced division of contributions from industry and academia, and includes a comprehensive, up-to-date bibliography covering all major publications in geophysical applications of ANNs and FZ. A special feature of this volume is the preface written by Professor Fred Aminzadeh, eminent authority in the field of artificial intelligence and geophysics. The enclosed CD-ROM contains full colour figures and searchable files, as well as short biographies of the editors.

Hierarchical Neural Networks for Image Interpretation

Автор: Behnke Sven
Название: Hierarchical Neural Networks for Image Interpretation
ISBN: 3540407227 ISBN-13(EAN): 9783540407225
Издательство: Springer
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Цена: 10394 р.
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Описание: Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains.This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.

Introduction to statistical relational learning

Название: Introduction to statistical relational learning
ISBN: 0262072882 ISBN-13(EAN): 9780262072885
Издательство: MIT Press
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Цена: 9039 р.
Наличие на складе: Нет в наличии.

Описание: Describes advanced statistical modeling and knowledge representation techniques for an area of machine learning and probabilistic reasoning. This volume includes introductory material, tutorials for different proposed approaches, and applications.

Neural Networks and the Financial Markets / Predicting, Combining and Portfolio Optimisation

Автор: Shadbolt Jimmy, Taylor John G.
Название: Neural Networks and the Financial Markets / Predicting, Combining and Portfolio Optimisation
ISBN: 1852335319 ISBN-13(EAN): 9781852335311
Издательство: Springer
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Цена: 22268 р.
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Описание: This volume looks at financial prediction from a broad range of perspectives. It covers: - the economic arguments - the practicalities of the markets - how predictions are used - how predictions are made - how predictions are turned into something usable (asset locations) It combines a discussion of standard theory with state-of-the-art material on a wide range of information processing techniques as applied to cutting-edge financial problems. All the techniques are demonstrated with real examples using actual market data, and show that it is possible to extract information from very noisy, sparse data sets. Aimed primarily at researchers in financial prediction, time series analysis and information processing, this book will also be of interest to quantitative fund managers and other professionals involved in financial prediction.

Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence / 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13-15, 2001, Proceedings, Part I

Автор: Mira Jose, Prieto Alberto
Название: Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence / 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13-15, 2001, Proceedings, Part I
ISBN: 3540422358 ISBN-13(EAN): 9783540422358
Издательство: Springer
Цена: 17819 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes, together with its companion, LNCS 2085, the refereed proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, held in Granada, Spain, in June 2001. The 200 revised papers presented were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in sections on foundations of connectionism, biophysical models of neurons, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, artificial intelligence and congnitive processes, methodology for nets design, nets simulation and implementation, bio-inspired systems and engineering, and other applications in a variety of fields.

Artificial Neural Nets. Problem Solving Methods / 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003, MaГі, Menorca, Spain, June 3-6. Proceedings, Part II

Автор: Mira JosГ©, Alvarez JosГ© R.
Название: Artificial Neural Nets. Problem Solving Methods / 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003, MaГі, Menorca, Spain, June 3-6. Proceedings, Part II
ISBN: 354040211X ISBN-13(EAN): 9783540402114
Издательство: Springer
Цена: 16328 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The two-volume set LNCS 2686 and LNCS 2687 constitute the refereed proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003, held in MaГі, Menorca, Spain in June 2003. 

Models of Neural Networks IV / Early Vision and Attention

Автор: Hemmen Leo van, Cowan Jack, Domany Eytan
Название: Models of Neural Networks IV / Early Vision and Attention
ISBN: 0387951059 ISBN-13(EAN): 9780387951058
Издательство: Springer
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Цена: 11879 р.
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Описание: With no effort we scan a scene by directing our gaze at specific objects, discerning them individually despite the background of other objects, contours, shadows, and changes in illumination. The process is partially intentional, partially automatic, and entirely amazing: no machine can accomplish this, but the simplest insect can. A single glance captures megabytes of data; we reduce this flood by singling out specific objects for attention. This volume, with chapters by leading researchers in the field, is devoted to early vision and attention, that is, to the first stages of visual information processing.John Hertz, who has extensive experience in both computational and experimental neuroscience, provides a theoretical introduction to neural modeling. John Van Opstal explains how the gaze is controlled and presents a novel theory incorporating recent experimental results. Klaus Funke and his colleagues describe the anatomy, physiology, functional relations, and ensuing response properties of the first stages in visual information processing; they provide one of the most comprehensive reviews available at the moment. Reinhard Eckhorn explains the underlying principles of scene segmentation. Esther Peterhans and her coworkers analyze a model of figure-ground segregation and brightness perception at illusory contours. Ernst Niebur and his collaborators indicate how visual attention can be controlled; Julian Eggert and Leo van Hemmen elucidate the feedback mechanism proper. Rob de Ruyter van Steveninck and Bill Bialek show how insects process visual information with impressive efficiency. Finally, Wolfgang Maass describes paradigms for computing with spiking neurons from the point of view of a computer scientist.

Fully Tuned Radial Basis Function Neural Networks for Flight Control

Автор: Sundararajan N., Saratchandran P., Yan Li
Название: Fully Tuned Radial Basis Function Neural Networks for Flight Control
ISBN: 0792375181 ISBN-13(EAN): 9780792375180
Издательство: Springer
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Цена: 24979 р.
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Описание: 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.

Advances in Neural Networks - ISNN 2004 / International Symposium on Neural Networks, Dalian, China, August 19-21, 2004, Proceedings, Part I

Автор: Yin Fuliang, Wang Jun, Guo Chengan
Название: Advances in Neural Networks - ISNN 2004 / International Symposium on Neural Networks, Dalian, China, August 19-21, 2004, Proceedings, Part I
ISBN: 3540228411 ISBN-13(EAN): 9783540228417
Издательство: Springer
Цена: 25244 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The two volume set LNCS 3173/3174 constitutes the refereed proceedings of the International Symposium on Neural Networks, ISNN 2004, held in Dalian, China in August 2004.The 329 papers presented were carefully reviewed and selected from more than 800 submissions. The papers span the entire scope of neural computing and its applications; they are organized in 11 major topical parts on theoretical analysis; learning and optimization; support vector machines; blind source separation, independent component analysis, and principal component analysis; clustering and classification; robotics and control; telecommunications; signal image, and time series analysis; biomedical applications; detection, diagnosis, and computer security; and other applications.

Control of Flexible-link Manipulators Using Neural Networks

Автор: Talebi H.A., Patel R.V., Khorasani K.
Название: Control of Flexible-link Manipulators Using Neural Networks
ISBN: 1852334096 ISBN-13(EAN): 9781852334093
Издательство: Springer
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Цена: 14849 р.
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Описание: Control of Flexible-link Manipulators Using Neural Networks addresses the difficulties that arise in controlling the end-point of a manipulator that has a significant amount of structural flexibility in its links. The non-minimum phase characteristic, coupling effects, nonlinearities, parameter variations and unmodeled dynamics in such a manipulator all contribute to these difficulties. Control strategies that ignore these uncertainties and nonlinearities generally fail to provide satisfactory closed-loop performance. This monograph develops and experimentally evaluates several intelligent (neural network based) control techniques to address the problem of controlling the end-point of flexible-link manipulators in the presence of all the aforementioned difficulties. To highlight the main issues, a very flexible-link manipulator whose hub exhibits a considerable amount of friction is considered for the experimental work. Four different neural network schemes are proposed and implemented on the experimental test-bed. The neural networks are trained and employed as online controllers.

Pattern Recognition and Neural Networks

Автор: Brian D. Ripley
Название: Pattern Recognition and Neural Networks
ISBN: 0521717701 ISBN-13(EAN): 9780521717700
Издательство: Cambridge Academ
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Цена: 7591 р.
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Описание: Now in paperback: the most reliable account of the statistical framework for pattern recognition and machine learning. With unparalleled coverage and a wealth of case-studies this book gives valuable insight into both the theory and the enormously diverse applications (which can be found in remote sensing, astrophysics, engineering and medicine, for example). So that readers can develop their skills and understanding, many of the real data sets used in the book are available from the author’s website: www.stats.ox.ac.uk/~ripley/PRbook/. For the same reason, many examples are included to illustrate real problems in pattern recognition. Unifying principles are highlighted, and the author gives an overview of the state of the subject, making the book valuable to experienced researchers in statistics, machine learning/artificial intelligence and engineering. The clear writing style means that the book is also a superb introduction for non-specialists.


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