Neural Networks

A Systematic Introduction

Author: Raul Rojas

Publisher: Springer Science & Business Media

ISBN: 3642610684

Category: Computers

Page: 502

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Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.
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Artificial Neural Networks for Speech and Vision

Author: Richard J. Mammone

Publisher: Chapman & Hall

ISBN: N.A

Category: Computers

Page: 586

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Presents some of the most promising current research in the design and training of artificial neural networks (ANNs) with applications in speech and vision, as reported by the investigators themselves. The volume is divided into three sections. The first gives an overview of the general field of ANN.
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The Handbook of Brain Theory and Neural Networks

Author: Michael A. Arbib,Fletcher Jones Professor of Computer Science and Professor of Biological Sciences Biomedical Engineering Neuroscience and Psychology Michael A Arbib,Prudence H. Arbib

Publisher: MIT Press

ISBN: 0262011972

Category: Computers

Page: 1290

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This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions: how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).
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Advances in Neural Networks – ISNN 2015

12th International Symposium on Neural Networks, ISNN 2015, Jeju, South Korea, October 15-18, 2015, Proceedings

Author: Xiaolin Hu,Yousheng Xia,Yunong Zhang,Dongbin Zhao

Publisher: Springer

ISBN: 331925393X

Category: Computers

Page: 510

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The volume LNCS 9377 constitutes the refereed proceedings of the 12th International Symposium on Neural Networks, ISNN 2015, held in Jeju, South Korea in October 2015. The 55 revised full papers presented were carefully reviewed and selected from 97 submissions. These papers cover many topics of neural network-related research including intelligent control, neurodynamic analysis, memristive neurodynamics, computer vision, signal processing, machine learning, and optimization.
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Concepts for Neural Networks

A Survey

Author: Lawrence J. Landau

Publisher: Springer Science & Business Media

ISBN: 1447134273

Category: Computers

Page: 312

View: 9450

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Concepts for Neural Networks - A Survey provides a wide-ranging survey of concepts relating to the study of neural networks. It includes chapters explaining the basics of both artificial neural networks and the mathematics of neural networks, as well as chapters covering the more philosophical background to the topic and consciousness. There is also significant emphasis on the practical use of the techniques described in the area of robotics. Containing contributions from some of the world's leading specialists in their fields (including Dr. Ton Coolen and Professor Igor Aleksander), this volume will provide the reader with a good, general introduction to the basic concepts needed to understan d and use neural network technology.
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Artificial Neural Networks

Methodological Advances and Biomedical Applications

Author: Kenji Suzuki

Publisher: BoD – Books on Demand

ISBN: 9533072431

Category: Computers

Page: 376

View: 2875

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Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications in various areas. The purpose of this book is to provide recent advances of artificial neural networks in biomedical applications. The book begins with fundamentals of artificial neural networks, which cover an introduction, design, and optimization. Advanced architectures for biomedical applications, which offer improved performance and desirable properties, follow. Parts continue with biological applications such as gene, plant biology, and stem cell, medical applications such as skin diseases, sclerosis, anesthesia, and physiotherapy, and clinical and other applications such as clinical outcome, telecare, and pre-med student failure prediction. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks in biomedical areas. The target audience includes professors and students in engineering and medical schools, researchers and engineers in biomedical industries, medical doctors, and healthcare professionals.
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Artificial Neural Networks for Engineers and Scientists

Solving Ordinary Differential Equations

Author: S. Chakraverty,Susmita Mall

Publisher: CRC Press

ISBN: 1351651315

Category: Mathematics

Page: 150

View: 7918

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Differential equations play a vital role in the fields of engineering and science. Problems in engineering and science can be modeled using ordinary or partial differential equations. Analytical solutions of differential equations may not be obtained easily, so numerical methods have been developed to handle them. Machine intelligence methods, such as Artificial Neural Networks (ANN), are being used to solve differential equations, and these methods are presented in Artificial Neural Networks for Engineers and Scientists: Solving Ordinary Differential Equations. This book shows how computation of differential equation becomes faster once the ANN model is properly developed and applied.
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Neural Networks for Applied Sciences and Engineering

From Fundamentals to Complex Pattern Recognition

Author: Sandhya Samarasinghe

Publisher: CRC Press

ISBN: 9781420013061

Category: Computers

Page: 570

View: 5395

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In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks. Beginning with an introductory discussion on the role of neural networks in scientific data analysis, this book provides a solid foundation of basic neural network concepts. It contains an overview of neural network architectures for practical data analysis followed by extensive step-by-step coverage on linear networks, as well as, multi-layer perceptron for nonlinear prediction and classification explaining all stages of processing and model development illustrated through practical examples and case studies. Later chapters present an extensive coverage on Self Organizing Maps for nonlinear data clustering, recurrent networks for linear nonlinear time series forecasting, and other network types suitable for scientific data analysis. With an easy to understand format using extensive graphical illustrations and multidisciplinary scientific context, this book fills the gap in the market for neural networks for multi-dimensional scientific data, and relates neural networks to statistics. Features § Explains neural networks in a multi-disciplinary context § Uses extensive graphical illustrations to explain complex mathematical concepts for quick and easy understanding ? Examines in-depth neural networks for linear and nonlinear prediction, classification, clustering and forecasting § Illustrates all stages of model development and interpretation of results, including data preprocessing, data dimensionality reduction, input selection, model development and validation, model uncertainty assessment, sensitivity analyses on inputs, errors and model parameters Sandhya Samarasinghe obtained her MSc in Mechanical Engineering from Lumumba University in Russia and an MS and PhD in Engineering from Virginia Tech, USA. Her neural networks research focuses on theoretical understanding and advancements as well as practical implementations.
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An Introduction to Neural Computing

Author: Igor Aleksander,Helen Morton

Publisher: Itp - Media

ISBN: N.A

Category: Computers

Page: 284

View: 1742

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The second edition of this text has been updated and includes material on new developments including neurocontrol, pattern analysis and dynamic systems. The book should be useful for undergraduate students of neural networks.
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Hybrid Modeling and Optimization of Manufacturing

Combining Artificial Intelligence and Finite Element Method

Author: Ramón Quiza,Omar López-Armas,J. Paulo Davim

Publisher: Springer Science & Business Media

ISBN: 3642280846

Category: Computers

Page: 95

View: 1465

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Artificial intelligence (AI) techniques and the finite element method (FEM) are both powerful computing tools, which are extensively used for modeling and optimizing manufacturing processes. The combination of these tools has resulted in a new flexible and robust approach as several recent studies have shown. This book aims to review the work already done in this field as well as to expose the new possibilities and foreseen trends. The book is expected to be useful for postgraduate students and researchers, working in the area of modeling and optimization of manufacturing processes.
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