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Neural Computation


Neural Computation
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Handbook Of Neural Computation


Handbook Of Neural Computation
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Author : Pijush Samui
language : en
Publisher: Academic Press
Release Date : 2017-07-18

Handbook Of Neural Computation written by Pijush Samui and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-18 with Technology & Engineering categories.


Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods



Introduction To The Theory Of Neural Computation


Introduction To The Theory Of Neural Computation
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Author : John A. Hertz
language : en
Publisher: CRC Press
Release Date : 2018-03-08

Introduction To The Theory Of Neural Computation written by John A. Hertz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-08 with Science categories.


Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.



Neural Computation


Neural Computation
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Author : G. A. Orchard
language : en
Publisher: Taylor & Francis
Release Date : 1991

Neural Computation written by G. A. Orchard and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Computers categories.




From Natural To Artificial Neural Computation


From Natural To Artificial Neural Computation
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Author : Jose Mira
language : en
Publisher: Springer Science & Business Media
Release Date : 1995-05-24

From Natural To Artificial Neural Computation written by Jose Mira and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-05-24 with Computers categories.


This volume presents the proceedings of the International Workshop on Artificial Neural Networks, IWANN '95, held in Torremolinos near Malaga, Spain in June 1995. The book contains 143 revised papers selected from a wealth of submissions and five invited contributions; it covers all current aspects of neural computation and presents the state of the art of ANN research and applications. The papers are organized in sections on neuroscience, computational models of neurons and neural nets, organization principles, learning, cognitive science and AI, neurosimulators, implementation, neural networks for perception, and neural networks for communication and control.



Theoretical Advances In Neural Computation And Learning


Theoretical Advances In Neural Computation And Learning
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Author : Vwani Roychowdhury
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Theoretical Advances In Neural Computation And Learning written by Vwani Roychowdhury and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


For any research field to have a lasting impact, there must be a firm theoretical foundation. Neural networks research is no exception. Some of the founda tional concepts, established several decades ago, led to the early promise of developing machines exhibiting intelligence. The motivation for studying such machines comes from the fact that the brain is far more efficient in visual processing and speech recognition than existing computers. Undoubtedly, neu robiological systems employ very different computational principles. The study of artificial neural networks aims at understanding these computational prin ciples and applying them in the solutions of engineering problems. Due to the recent advances in both device technology and computational science, we are currently witnessing an explosive growth in the studies of neural networks and their applications. It may take many years before we have a complete understanding about the mechanisms of neural systems. Before this ultimate goal can be achieved, an swers are needed to important fundamental questions such as (a) what can neu ral networks do that traditional computing techniques cannot, (b) how does the complexity of the network for an application relate to the complexity of that problem, and (c) how much training data are required for the resulting network to learn properly? Everyone working in the field has attempted to answer these questions, but general solutions remain elusive. However, encouraging progress in studying specific neural models has been made by researchers from various disciplines.



Self Organizing Map Formation


Self Organizing Map Formation
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Author : Klaus Obermayer
language : en
Publisher: MIT Press
Release Date : 2001

Self Organizing Map Formation written by Klaus Obermayer and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Neural computers categories.


This book provides an overview of self-organizing map formation, including recent developments. Self-organizing maps form a branch of unsupervised learning, which is the study of what can be determined about the statistical properties of input data without explicit feedback from a teacher. The articles are drawn from the journal Neural Computation.The book consists of five sections. The first section looks at attempts to model the organization of cortical maps and at the theory and applications of the related artificial neural network algorithms. The second section analyzes topographic maps and their formation via objective functions. The third section discusses cortical maps of stimulus features. The fourth section discusses self-organizing maps for unsupervised data analysis. The fifth section discusses extensions of self-organizing maps, including two surprising applications of mapping algorithms to standard computer science problems: combinatorial optimization and sorting. Contributors J. J. Atick, H. G. Barrow, H. U. Bauer, C. M. Bishop, H. J. Bray, J. Bruske, J. M. L. Budd, M. Budinich, V. Cherkassky, J. Cowan, R. Durbin, E. Erwin, G. J. Goodhill, T. Graepel, D. Grier, S. Kaski, T. Kohonen, H. Lappalainen, Z. Li, J. Lin, R. Linsker, S. P. Luttrell, D. J. C. MacKay, K. D. Miller, G. Mitchison, F. Mulier, K. Obermayer, C. Piepenbrock, H. Ritter, K. Schulten, T. J. Sejnowski, S. Smirnakis, G. Sommer, M. Svensen, R. Szeliski, A. Utsugi, C. K. I. Williams, L. Wiskott, L. Xu, A. Yuille, J. Zhang



Unsupervised Learning


Unsupervised Learning
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Author : Geoffrey Hinton
language : en
Publisher: MIT Press
Release Date : 1999-05-24

Unsupervised Learning written by Geoffrey Hinton and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-05-24 with Medical categories.


Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.



Neural Codes And Distributed Representations


Neural Codes And Distributed Representations
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Author : L. F. Abbott
language : en
Publisher: MIT Press
Release Date : 1999

Neural Codes And Distributed Representations written by L. F. Abbott and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Coding theory categories.


Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. The present volume focuses on neural codes and representations, topics of broad interest to neuroscientists and modelers. The topics addressed are: how neurons encode information through action potential firing patterns, how populations of neurons represent information, and how individual neurons use dendritic processing and biophysical properties of synapses to decode spike trains. The papers encompass a wide range of levels of investigation, from dendrites and neurons to networks and systems.



Quantum Neural Computation


Quantum Neural Computation
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Author : Vladimir G. Ivancevic
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-01-18

Quantum Neural Computation written by Vladimir G. Ivancevic and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-18 with Computers categories.


Quantum Neural Computation is a graduate–level monographic textbook. It presents a comprehensive introduction, both non-technical and technical, into modern quantum neural computation, the science behind the fiction movie Stealth. Classical computing systems perform classical computations (i.e., Boolean operations, such as AND, OR, NOT gates) using devices that can be described classically (e.g., MOSFETs). On the other hand, quantum computing systems perform classical computations using quantum devices (quantum dots), that is devices that can be described only using quantum mechanics. Any information transfer between such computing systems involves a state measurement. This book describes this information transfer at the edge of classical and quantum chaos and turbulence, where mysterious quantum-mechanical linearity meets even more mysterious brain’s nonlinear complexity, in order to perform a super–high–speed and error–free computations. This monograph describes a crossroad between quantum field theory, brain science and computational intelligence.



Introduction To The Theory Of Neural Computation


Introduction To The Theory Of Neural Computation
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Author : John A. Hertz
language : en
Publisher: CRC Press
Release Date : 2018-03-08

Introduction To The Theory Of Neural Computation written by John A. Hertz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-08 with Science categories.


Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.