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E-books in Neural Networks category by Christian Dawson - MDPI AG, 2016 This Special Issue focuses on the application of neural networks to a diverse range of fields and problems. It collates contributions concerning neural network applications in areas such as engineering, hydrology and medicine. ( 1755 views) by Martin T. Hagan, et al., 2014 This book provides a clear and detailed coverage of fundamental neural network architectures and learning rules. In it, the authors emphasize a coherent presentation of the principal neural networks, methods for training them and their applications.

( 2683 views) by Milan Hajek - University of KwaZulu-Natal, 2005 Contents: Introduction; Learning process; Perceptron; Back-propagation networks; The Hopfield network; Self-organizing feature maps; Temporal processing with neural networks; Radial-basis function networks; Adaline (Adaptive Linear System). ( 1791 views) by Kenji Suzuki (ed.) - InTech, 2013 Artificial neural networks may be the single most successful technology in the last two decades.

The purpose of this book is to provide recent advances in architectures, methodologies, and applications of artificial neural networks. ( 9540 views) - Wikibooks, 2010 Neural networks excel in a number of problem areas where conventional von Neumann computer systems have traditionally been slow and inefficient. Product Key Of Gx Works 2. This book is going to discuss the creation and use of artificial neural networks. ( 9442 views) by Todd Troyer - University of Texas at San Antonio, 2005 These notes have three main objectives: to present the major concepts of computational neuroscience, to present the basic mathematics that underlies these concepts, and to give the reader some idea of common approaches taken by neuroscientists. ( 4687 views) by Ben Krose, Patrick van der Smagt, 1996 This manuscript attempts to provide the reader with an insight in artificial neural networks. The choice of describing robotics and vision as neural network applications coincides with the neural network research interests of the authors. ( 9557 views) by Rolf Pfeifer, Dana Damian, Rudolf Fuchslin - University of Zurich, 2010 Systematic introduction to neural networks, biological foundations; important network classes and learning algorithms; supervised models (perceptrons, adalines, multi-layer perceptrons), support-vector machines, echo-state networks, etc.