Process Neural Networks

Process Neural Networks PDF Author: Xingui He
Publisher: Springer Science & Business Media
ISBN: 3540737626
Category : Computers
Languages : en
Pages : 240

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Book Description
For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.

Process Neural Networks

Process Neural Networks PDF Author: Xingui He
Publisher: Springer Science & Business Media
ISBN: 3540737626
Category : Computers
Languages : en
Pages : 240

Get Book Here

Book Description
For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.

Advances in Neural Information Processing Systems 17

Advances in Neural Information Processing Systems 17 PDF Author: Lawrence K. Saul
Publisher: MIT Press
ISBN: 9780262195348
Category : Computers
Languages : en
Pages : 1710

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Book Description
Papers presented at NIPS, the flagship meeting on neural computation, held in December 2004 in Vancouver.The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees--physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only twenty-five percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains the papers presented at the December, 2004 conference, held in Vancouver.

Advances in Neural Information Processing Systems 15

Advances in Neural Information Processing Systems 15 PDF Author: Suzanna Becker
Publisher: MIT Press
ISBN: 9780262025508
Category : Computers
Languages : en
Pages : 1738

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Book Description
Proceedings of the 2002 Neural Information Processing Systems Conference.

Advances in Neural Information Processing Systems 13

Advances in Neural Information Processing Systems 13 PDF Author: Todd K. Leen
Publisher: MIT Press
ISBN: 9780262122412
Category : Computers
Languages : en
Pages : 1136

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Book Description
The proceedings of the 2000 Neural Information Processing Systems (NIPS) Conference.The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. The conference is interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, vision, speech and signal processing, reinforcement learning and control, implementations, and diverse applications. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented at the 2000 conference.

Neural Networks: Computational Models and Applications

Neural Networks: Computational Models and Applications PDF Author: Huajin Tang
Publisher: Springer Science & Business Media
ISBN: 3540692258
Category : Computers
Languages : en
Pages : 310

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Book Description
Neural Networks: Computational Models and Applications presents 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. The book offers a compact, insightful understanding of the broad and rapidly growing neural networks domain.

Practical Applications of Sparse Modeling

Practical Applications of Sparse Modeling PDF Author: Irina Rish
Publisher: MIT Press
ISBN: 0262027720
Category : Computers
Languages : en
Pages : 265

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Book Description
"Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional data sets. This collection describes key approaches in sparse modeling, focusing on its applications in such fields as neuroscience, computational biology, and computer vision. Sparse modeling methods can improve the interpretability of predictive models and aid efficient recovery of high-dimensional unobserved signals from a limited number of measurements. Yet despite significant advances in the field, a number of open issues remain when sparse modeling meets real-life applications. The book discusses a range of practical applications and state-of-the-art approaches for tackling the challenges presented by these applications. Topics considered include the choice of method in genomics applications; analysis of protein mass-spectrometry data; the stability of sparse models in brain imaging applications; sequential testing approaches; algorithmic aspects of sparse recovery; and learning sparse latent models"--Jacket.

Advances in Neural Information Processing Systems 9

Advances in Neural Information Processing Systems 9 PDF Author: Michael C. Mozer
Publisher: MIT Press
ISBN: 9780262100656
Category : Computers
Languages : en
Pages : 1128

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Book Description
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes neural networks and genetic algorithms, cognitive science, neuroscience and biology, computer science, AI, applied mathematics, physics, and many branches of engineering. Only about 30% of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. All of the papers presented appear in these proceedings.

Advances in Neural Information Processing Systems 19

Advances in Neural Information Processing Systems 19 PDF Author: Bernhard Schölkopf
Publisher: MIT Press
ISBN: 0262195682
Category : Artificial intelligence
Languages : en
Pages : 1668

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Book Description
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.

Probabilistic Models of the Brain

Probabilistic Models of the Brain PDF Author: Rajesh P.N. Rao
Publisher: MIT Press
ISBN: 9780262264327
Category : Medical
Languages : en
Pages : 348

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Book Description
A survey of probabilistic approaches to modeling and understanding brain function. Neurophysiological, neuroanatomical, and brain imaging studies have helped to shed light on how the brain transforms raw sensory information into a form that is useful for goal-directed behavior. A fundamental question that is seldom addressed by these studies, however, is why the brain uses the types of representations it does and what evolutionary advantage, if any, these representations confer. It is difficult to address such questions directly via animal experiments. A promising alternative is to use probabilistic principles such as maximum likelihood and Bayesian inference to derive models of brain function. This book surveys some of the current probabilistic approaches to modeling and understanding brain function. Although most of the examples focus on vision, many of the models and techniques are applicable to other modalities as well. The book presents top-down computational models as well as bottom-up neurally motivated models of brain function. The topics covered include Bayesian and information-theoretic models of perception, probabilistic theories of neural coding and spike timing, computational models of lateral and cortico-cortical feedback connections, and the development of receptive field properties from natural signals.

Advances in Neural Information Processing Systems 10

Advances in Neural Information Processing Systems 10 PDF Author: Michael I. Jordan
Publisher: MIT Press
ISBN: 9780262100762
Category : Computers
Languages : en
Pages : 1114

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Book Description
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.