Neural Network Analysis Architectures And Applications

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Neural Network Analysis Architectures And Applications

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Author : A Browne
language : en
Publisher: CRC Press
Release Date : 2024-12-11

Neural Network Analysis Architectures And Applications written by A Browne and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-11 with Science categories.

Neural Network Analysis, Architectures and Applications discusses the main areas of neural networks, with each authoritative chapter covering the latest information from different perspectives. Divided into three parts, the book first lays the groundwork for understanding and simplifying networks. It then describes novel architectures and algorithms, including pulse-stream techniques, cellular neural networks, and multiversion neural computing. The book concludes by examining various neural network applications, such as neuron-fuzzy control systems and image compression. This final part of the book also provides a case study involving oil spill detection. This book is invaluable for students and practitioners who have a basic understanding of neural computing yet want to broaden and deepen their knowledge of the field.

Neural Network Analysis Architectures And Applications

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Author : A Browne
language : en
Publisher: CRC Press
Release Date : 1997-01-01

Neural Network Analysis Architectures And Applications written by A Browne and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-01-01 with Mathematics categories.

Neural Network Analysis, Architectures and Applications discusses the main areas of neural networks, with each authoritative chapter covering the latest information from different perspectives. Divided into three parts, the book first lays the groundwork for understanding and simplifying networks. It then describes novel architectures and algorithms, including pulse-stream techniques, cellular neural networks, and multiversion neural computing. The book concludes by examining various neural network applications, such as neuron-fuzzy control systems and image compression. This final part of the book also provides a case study involving oil spill detection. This book is invaluable for students and practitioners who have a basic understanding of neural computing yet want to broaden and deepen their knowledge of the field.

Neural Network Design

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Author : Martin T. Hagan
language : en
Publisher:
Release Date : 2003

Neural Network Design written by Martin T. Hagan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Neural networks (Computer science) categories.

Applications Of Neural Networks

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Author : Alan Murray
language : en
Publisher: Springer Science & Business Media
Release Date : 1994-12-31

Applications Of Neural Networks written by Alan Murray 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 1994-12-31 with Computers categories.

Applications of Neural Networks gives a detailed description of 13 practical applications of neural networks, selected because the tasks performed by the neural networks are real and significant. The contributions are from leading researchers in neural networks and, as a whole, provide a balanced coverage across a range of application areas and algorithms. The book is divided into three sections. Section A is an introduction to neural networks for nonspecialists. Section B looks at examples of applications using `Supervised Training'. Section C presents a number of examples of `Unsupervised Training'. For neural network enthusiasts and interested, open-minded sceptics. The book leads the latter through the fundamentals into a convincing and varied series of neural success stories -- described carefully and honestly without over-claiming. Applications of Neural Networks is essential reading for all researchers and designers who are tasked with using neural networks in real life applications.

Fundamentals Of Neural Networks

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Author : Fausett
language : en
Publisher: Prentice Hall
Release Date : 1994

Fundamentals Of Neural Networks written by Fausett and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.

Automatic Generation Of Neural Network Architecture Using Evolutionary Computation

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Author : E. Vonk
language : en
Publisher: World Scientific
Release Date : 1997

Automatic Generation Of Neural Network Architecture Using Evolutionary Computation written by E. Vonk and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.

This book describes the application of evolutionary computation in the automatic generation of a neural network architecture. The architecture has a significant influence on the performance of the neural network. It is the usual practice to use trial and error to find a suitable neural network architecture for a given problem. The process of trial and error is not only time-consuming but may not generate an optimal network. The use of evolutionary computation is a step towards automation in neural network architecture generation.An overview of the field of evolutionary computation is presented, together with the biological background from which the field was inspired. The most commonly used approaches to a mathematical foundation of the field of genetic algorithms are given, as well as an overview of the hybridization between evolutionary computation and neural networks. Experiments on the implementation of automatic neural network generation using genetic programming and one using genetic algorithms are described, and the efficacy of genetic algorithms as a learning algorithm for a feedforward neural network is also investigated.

Principal Component Neural Networks

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Author : K. I. Diamantaras
language : en
Publisher: Wiley-Interscience
Release Date : 1996-03-08

Principal Component Neural Networks written by K. I. Diamantaras and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-03-08 with Computers categories.

Systematically explores the relationship between principal component analysis (PCA) and neural networks. Provides a synergistic examination of the mathematical, algorithmic, application and architectural aspects of principal component neural networks. Using a unified formulation, the authors present neural models performing PCA from the Hebbian learning rule and those which use least squares learning rules such as back-propagation. Examines the principles of biological perceptual systems to explain how the brain works. Every chapter contains a selected list of applications examples from diverse areas.

Neural Networks

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Author : Gérard Dreyfus
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-11-25

Neural Networks written by Gérard Dreyfus 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 2005-11-25 with Science categories.

Neural networks represent a powerful data processing technique that has reached maturity and broad application. When clearly understood and appropriately used, they are a mandatory component in the toolbox of any engineer who wants make the best use of the available data, in order to build models, make predictions, mine data, recognize shapes or signals, etc. Ranging from theoretical foundations to real-life applications, this book is intended to provide engineers and researchers with clear methodologies for taking advantage of neural networks in industrial, financial or banking applications, many instances of which are presented in the book. For the benefit of readers wishing to gain deeper knowledge of the topics, the book features appendices that provide theoretical details for greater insight, and algorithmic details for efficient programming and implementation. The chapters have been written by experts and edited to present a coherent and comprehensive, yet not redundant, practically oriented introduction.

Business Intelligence For Enterprise Internet Of Things

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Author : Anandakumar Haldorai
language : en
Publisher: Springer Nature
Release Date : 2020-06-09

Business Intelligence For Enterprise Internet Of Things written by Anandakumar Haldorai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-09 with Technology & Engineering categories.

This book discusses Internet of Things (IoT) as it relates to enterprise applications, systems, and infrastructures. The authors discuss IoT and how it’s disrupting industries such as enterprise manufacturing, enterprise transportation, enterprise smart market, enterprise utilities, and enterprise healthcare. They cover how IoT in the enterprise will have a major impact on the lives of consumers and professionals around the world and how it will change the way we think about professional and consumer networks. The book's topics include IoT enterprise system architecture, IoT enabling enterprise technologies, and IoT enterprise services and applications. Examples include enterprise on demand, market impacts, and implications on smart technologies, big data enterprise management, and future enterprise Internet design for various IoT use cases, such as share markets, healthcare, smart cities, smart environments, smart communications and smart homes.

Deep Learning Architectures

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Author : Ovidiu Calin
language : en
Publisher: Springer Nature
Release Date : 2020-02-13

Deep Learning Architectures written by Ovidiu Calin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-13 with Mathematics categories.

This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter. This book can be used in a graduate course in deep learning, with the first few parts being accessible to senior undergraduates. In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject.