Автор: Brian D. Ripley Название: Pattern Recognition and Neural Networks ISBN: 0521717701 ISBN-13(EAN): 9780521717700 Издательство: Cambridge Academ Рейтинг: Цена: 3746 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Bishop, Christopher M. Название: Neural Networks for Pattern Recognition ISBN: 0198538642 ISBN-13(EAN): 9780198538646 Издательство: Oxford Academ Рейтинг: Цена: 4683 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Rolls, Edmund (Professor, Department of Experiment Название: Neural Networks and Brain Function ISBN: 0198524323 ISBN-13(EAN): 9780198524328 Издательство: Oxford Academ Рейтинг: Цена: 4158 р. Наличие на складе: Поставка под заказ.
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.
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.
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.
Описание: This book constitutes the refereed proceedings of the joint International Conference on Artificial Neural Networks and International Conference on Neural Information Processing, ICANN/ICONIP 2003, held in Istanbul, Turkey, in June 2003.The 138 revised full papers were carefully reviewed and selected from 346 submissions. The papers are organized in topical sections on learning algorithms, support vector machine and kernel methods, statistical data analysis, pattern recognition, vision, speech recognition, robotics and control, signal processing, time-series prediction, intelligent systems, neural network hardware, cognitive science, computational neuroscience, context aware systems, complex-valued neural networks, emotion recognition, and applications in bioinformatics.
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.
Автор: Revesz Peter Название: Introduction to Constraint Databases ISBN: 0387987290 ISBN-13(EAN): 9780387987293 Издательство: Springer Рейтинг: Цена: 6540 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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.
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.
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.
Описание: 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, NovГЎk, S.-Y. Lee, Pedrycz, Raudys, Setiono, Sincak, Strumillo, Takagi, Usui, Wilamowski and Zurada. An excellent overview of soft computing methods and their applications.
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