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Kalman Filtering and Neural Networksby Simon Haykin
John Wiley & Sons, Inc. 2004; US$ 147.00State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear. The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter. Other chapters cover: An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF)... more...
An Introduction to Neural Networksby K. Gurney
Routledge 1997; US$ 59.95This undergraduate text introduces the fundamentals of neural networks in a gentle but practical fashion with minimal mathematics. It should be of use to students of computer science and engineering, and graduate students in the allied neural more...
Static and Dynamic Neural Networksby Madan M. Gupta; Liang Jin; Noriyasu Homma
John Wiley & Sons, Inc. 2004; US$ 200.00Provides comprehensive treatment of the theory of both static and dynamic neural networks. * Theoretical concepts are illustrated by reference to practical examples Includes end-of-chapter exercises and end-of-chapter exercises. *An Instructor Support FTP site is available from the Wiley editorial department. more...
Cellular Neural Networks and Visual Computingby Leon O. Chua; Tamas Roska
Cambridge University Press 2002; US$ 70.00This is a unique undergraduate level textbook on Cellular Nonlinear/neural Networks (CNN) technology. The many examples and excercises, including a simulator accessible via the Internet, make this book an ideal introduction to CNNs and analogic cellular computing for students, researchers and engineers from a wide range of backgrounds. more...
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Cambridge University Press 2001; US$ 66.00Artificial neural networks provide a simple framework for describing learning from examples. This coherent account of important concepts and techniques of statistical mechanics and their application to learning theory comes with background material in mathematics and physics, plus many examples and exercises, making it ideal for courses, self-teaching, or reference. more...
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Springer 2005; US$ 160.00The reader is presented an approach to the construction of a visual system, which is behaviorally, computationally and neurally motivated. The central goal is to characterize the process of visual categorization and to find a suitable representation format that can successfully deal with the structural variability existent within visual categories. It does not define such representations a priori but attempts to show directions on how to gradually work towards them. The book reviews past and existent theories of visual object and shape recognition in the fields of computer vision, neuroscience and psychology. The entire range of computations is discussed, as for example contour extraction in retinal circuits, orientation determination in cortical... more...
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World Scientific 2003; US$ 100.10Cellular computing is a natural information processing paradigm, capable of modeling various biological, physical and social phenomena, as well as other kinds of complex adaptive systems. The programming of a cellular computer is in many respects similar to the genetic evolution in biology, the result being a proper cell design and a task-specific gene. more...
Cellular Neural Networks, Multi-scroll Chaos And Synchronizationby Müstak E. Yalçin; Johan Suykens; Joos Vandewalle
World Scientific 2005; US$ 75.40For engineering applications that are based on nonlinear phenomena, novel information processing systems require new methodologies and design principles. This perspective is the basis of the three cornerstones of this book: cellular neural networks, chaos and synchronization. Cellular neural networks and their universal machine implementations offer a well-established platform for processing spatial-temporal patterns and wave computing. Multi-scroll circuits are generalizations to the original Chua?s circuit, leading to chip implementable circuits with increasingly complex attractors. Several applications make use of synchronization techniques for nonlinear systems. A systematic overview is given for Lur?e representable systems with global... more...
Methods and Procedures for the Verification and Validation of Artificial Neural Networksby Brian J. Taylor
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Limitations and Future Trends in Neural Computationby S. Ablameyko; L. Goras; M. Gori
IOS Press 2003; US$ 116.00This work reports critical analyses on complexity issues in the continuum setting and on generalization to new examples, which are two basic milestones in learning from examples in connectionist models. It also covers up-to-date developments in computational mathematics. more...
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