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Neural smithing :supervised learning in feedforward artificial neural networks
"A Bradford book.""Artificial neural networks are nonlinear mapping systems whose structure is loosely based on principles observed in the nervous systems of humans and animals. The basic idea is that massive systems of simple units linked together in appropriate ways can generate many complex and interesting behaviors. This book focuses on the subset of feedforward artificial neural networks c…
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- ISBN/ISSN
- 9780262282215
- Collation
- 1 online resource (viii, 346 pages) :illustrations
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The Neurobiology of neural networks
"A Bradford book."This timely overview and synthesis of recent work in both artificial neural networks and neurobiology seeks to examine neurobiological data from a network perspective and to encourage neuroscientists to participate in constructing the next generation of neural networks. Individual chapters were commissioned from selected authors to bridge the gap between present neural network…
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- ISBN/ISSN
- 0262290871
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- 1 online resource (xii, 227 pages) :illustrations.
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Advances in neural information processing systems 19 Proceedings of the 2006 …
The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation and machine learning. This volume contains the papers presented at the December 2006 meeting, held in Vancouver.
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- 1 online resource (xxiv, 1643 pages) : illustrations.
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Neurotechnology for biomimetic robots
"A Bradford book."An overview of neurotechnology, the engineering of robots based on animals and animal behavior.The goal of neurotechnology is to confer the performance advantages of animal systems on robotic machines. Biomimetic robots differ from traditional robots in that they are agile, relatively cheap, and able to deal with real-world environments. The engineering of these robots require…
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- ISBN/ISSN
- 9780262267496
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- 1 online resource (xiv, 636 pages) :illustrations
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Circuit Complexity and Neural Networks
Neural networks usually work adequately on small problems but can run into trouble when they are scaled up to problems involving large amounts of input data. Circuit Complexity and Neural Networks addresses the important question of how well neural networks scale - that is, how fast the computation time and number of neurons grow as the problem size increases. It surveys recent research in circ…
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- ISBN/ISSN
- 9780262281249
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- 1 online resource (xxix, 270 pages) :illustrations.
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New directions in statistical signal processing :from systems to brain
Signal processing and neural computation have separately and significantly influenced many disciplines, but the cross-fertilization of the two fields has begun only recently. Research now shows that each has much to teach the other, as we see highly sophisticated kinds of signal processing and elaborate hierachical levels of neural computation performed side by side in the brain. In New Directi…
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- ISBN/ISSN
- 9780262256315
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- 1 online resource (vi, 514 pages) :illustrations.
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Talking Nets: An Oral History of Neural Networks
A Bradford book."OCLC-licensed vendor bibliographic record.
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- ISBN/ISSN
- 9780262267151
- Collation
- 1 online resource (xi, 434 pages) :illustrations
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Independent component analysis : a tutorial introduction
"A Bradford book."Independent component analysis (ICA) is becoming an increasingly important tool for analyzing large data sets. In essence, ICA separates an observed set of signal mixtures into a set of statistically independent component signals, or source signals. In so doing, this powerful method can extract the relatively small amount of useful information typically found in large data set…
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- ISBN/ISSN
- 9780262257046
- Collation
- 1 online resource (xviii, 193 pages) : illustrations
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- Call Number
- 006 STO i
Connectionist symbol processing
"A Bradford book.""Reprinted from Artificial intelligence, an international journal, volume 46, numbers 1-2, 1990"--Title page verso.The six contributions in Connectionist Symbol Processing address the current tension within the artificial intelligence community between advocates of powerful symbolic representations that lack efficient learning procedures and advocates of relatively simple lear…
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- ISBN/ISSN
- 9780262256360
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- 1 online resource (262 pages) :illustrations.
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Pattern recognition by self-organizing neural networks
Pattern Recognition by Self-Organizing Neural Networks presents the most recent advances in an area of research that is becoming vitally important in the fields of cognitive science, neuroscience, artificial intelligence, and neural networks in general. Pattern Recognition by Self-Organizing Neural Networks presents the most recent advances in an area of research that is becoming vitally imp…
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- ISBN/ISSN
- 9780262269896
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- 1 online resource (691 pages) :illustrations
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