Fundamentals of Artificial Neural Networks PDF Download
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Author: Mohamad H. Hassoun
Publisher: MIT Press
ISBN: 9780262082396
Category : Computers
Languages : en
Pages : 546
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Book Description
A systematic account of artificial neural network paradigms that identifies fundamental concepts and major methodologies. Important results are integrated into the text in order to explain a wide range of existing empirical observations and commonly used heuristics.
Author: Mohamad H. Hassoun
Publisher: MIT Press
ISBN: 9780262082396
Category : Computers
Languages : en
Pages : 546
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Book Description
A systematic account of artificial neural network paradigms that identifies fundamental concepts and major methodologies. Important results are integrated into the text in order to explain a wide range of existing empirical observations and commonly used heuristics.
Author: Osval Antonio Montesinos López
Publisher: Springer Nature
ISBN: 3030890104
Category : Technology & Engineering
Languages : en
Pages : 707
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Book Description
This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Author: Zenon Waszczysznk
Publisher: Springer Science & Business Media
ISBN: 9783211833223
Category : Computers
Languages : en
Pages : 324
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Book Description
Neural Networks are a new, interdisciplinary tool for information processing. Neurocomputing being successfully introduced to structural problems which are difficult or even impossible to be analysed by standard computers (hard computing). The book is devoted to foundations and applications of NNs in the structural mechanics and design of structures.
Author: Fausett
Publisher: Prentice Hall
ISBN: 9780133367690
Category :
Languages : en
Pages : 300
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Book Description
Author: Daniel Graupe
Publisher: World Scientific
ISBN: 9814475564
Category : Computers
Languages : en
Pages : 320
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Book Description
The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural network approaches and architectures with the theories, this text presents detailed case studies for each of the approaches, accompanied with complete computer codes and the corresponding computed results. The case studies are designed to allow easy comparison of network performance to illustrate strengths and weaknesses of the different networks.
Author: Sandhya Samarasinghe
Publisher: CRC Press
ISBN: 1420013068
Category : Computers
Languages : en
Pages : 596
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Book Description
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
Author: Joao Luis Garcia Rosa
Publisher: BoD – Books on Demand
ISBN: 9535127047
Category : Computers
Languages : en
Pages : 416
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Book Description
The idea of simulating the brain was the goal of many pioneering works in Artificial Intelligence. The brain has been seen as a neural network, or a set of nodes, or neurons, connected by communication lines. Currently, there has been increasing interest in the use of neural network models. This book contains chapters on basic concepts of artificial neural networks, recent connectionist architectures and several successful applications in various fields of knowledge, from assisted speech therapy to remote sensing of hydrological parameters, from fabric defect classification to application in civil engineering. This is a current book on Artificial Neural Networks and Applications, bringing recent advances in the area to the reader interested in this always-evolving machine learning technique.
Author: Kevin Gurney
Publisher: CRC Press
ISBN: 1482286998
Category : Computers
Languages : en
Pages : 148
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Book Description
Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.
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.
Author: Nirmal K. Bose
Publisher: McGraw-Hill Companies
ISBN:
Category : Computers
Languages : en
Pages : 520
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Book Description
