Автор: Bishop, Christopher M.
Название: Neural Networks for Pattern Recognition
ISBN: 0198538642 ISBN-13(EAN): 9780198538646
Издательство: Oxford Academ
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Цена: 4190 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: Revesz Peter
Название: Introduction to Constraint Databases
ISBN: 0387987290 ISBN-13(EAN): 9780387987293
Издательство: Springer
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Цена: 6156 р.
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Описание: Presents the theory and applications of "constraint database" systems, which provide methods for the design of data models and query languages. This resource is useful for advanced students, practitioners, and professionals in computer science, database systems, and information systems.

Название: Introduction to statistical relational learning
ISBN: 0262072882 ISBN-13(EAN): 9780262072885
Издательство: Wiley
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Цена: 3735 р.
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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.

Автор: Brian D. Ripley
Название: Pattern Recognition and Neural Networks
ISBN: 0521717701 ISBN-13(EAN): 9780521717700
Издательство: Cambridge Academ
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Цена: 3352 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.

Автор: Rolls, Edmund (Professor, Department of Experiment
Название: Neural Networks and Brain Function
ISBN: 0198524323 ISBN-13(EAN): 9780198524328
Издательство: Oxford Academ
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Цена: 3720 р.
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Описание: Aims to describe the types of computation that can be performed by biologically plausible neural networks, and to show how these may be implemented in different systems in the brain. This book is suitable for researchers, graduate students and advanced undergraduates in the fields of neuroscience and artificial intelligence.

Автор: Mira Jose, Prieto Alberto
Название: Bio-Inspired Applications of Connectionism / 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13-15, 2001, Proceedings, Part II
ISBN: 3540422374 ISBN-13(EAN): 9783540422372
Издательство: Springer
Цена: 9239 р.
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Описание: This book constitutes, together with its companion LNCS 2084, 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 cognitive processes, methodology for nets design, nets simulation and implementation, bio-inspired systems and engineering, and other applications in a variety of fields.

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: 13196 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.

Автор: Dorffner Georg, Bischof Horst, Hornik Kurt
Название: Artificial Neural Networks - ICANN 2001 / International Conference Vienna, Austria, August 21-25, 2001 Proceedings
ISBN: 3540424865 ISBN-13(EAN): 9783540424864
Издательство: Springer
Цена: 12319 р.
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Описание: This book constitutes the refereed proceedings of the International Conference on Artificial Neural Networks,ICANN 2001, held in Vienna, Austria in August 2001. The 171 revised papers presented together with three invited contributions were carefully reviewed and selected from around 300 submissions. The papers are organized in topical sections on data analysis and pattern recognition, theory, kernel methods, topographic mapping, independent component analysis, signal processing, time series processing, agent-based economic modeling, selforganization and dynamical systems, robotics and control, vision and image processing, computational neuroscience, and connectionist and cognitive science.

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: 10559 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.

Автор: Dorronsoro Jose R.
Название: Artificial Neural Networks - ICANN 2002 / International Conference, Madrid, Spain, August 28-30, 2002. Proceedings
ISBN: 3540440747 ISBN-13(EAN): 9783540440741
Издательство: Springer
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Цена: 7039 р.
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Описание: This book constitutes the refereed proceedings of the International Conference on Artificial Neural Networks, ICANN 2002, held in Madrid, Spain in August 2002.The 221 revised papers presented were carefully reviewed and selected from more than 450 submissions. The book presents parts on computational neuroscience, connectionist cognitive science, data analysis and pattern recognition, kernel methods, robotics and control, selforganization, signal and time series analysis, and vision and image processing.

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: 7039 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.

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: 10559 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.