Overview
- Latest research on computational models and applications of neural networks
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 53)
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Table of contents (17 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Neural Networks: Computational Models and Applications covers a wealth of important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. By presenting various computational models, this book is developed to provide readers with a quick but insightful understanding of the broad and rapidly growing areas in the neural networks domain.
Besides laying down fundamentals on artificial neural networks, this book also studies biologically inspired neural networks. Some typical computational models are discussed, and subsequently applied to objection recognition, scene analysis and associative memory. The studies of bio-inspired models have important implications in computer vision and robotic navigation, as well as new efficient algorithms for image analysis. Another significant feature of the book is that it begins with fundamental dynamical problems in presenting the mathematical techniques extensively used in analyzing neurodynamics, thus allowing non-mathematicians to develop and apply these analytical techniques easily.
Written for a wide readership, engineers, computer scientists and mathematicians interested in machine learning, data mining and neural networks modeling will find this book of value. This book will also act as a helpful reference for graduate students studying neural networks and complex dynamical systems.
Authors and Affiliations
Bibliographic Information
Book Title: Neural Networks: Computational Models and Applications
Authors: Huajin Tang, Kay Chen Tan, Zhang Yi
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-69226-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2007
Hardcover ISBN: 978-3-540-69225-6Published: 12 March 2007
Softcover ISBN: 978-3-642-08871-1Published: 22 November 2010
eBook ISBN: 978-3-540-69226-3Published: 09 March 2007
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XXII, 300
Number of Illustrations: 103 b/w illustrations
Topics: Artificial Intelligence, Mathematical and Computational Engineering
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