From Natural To Artificial Neural Computation
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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.
From Natural To Artifical Neural Computation
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Author :
language : en
Publisher:
Release Date : 1995
From Natural To Artifical Neural Computation written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Artificial intelligence categories.
From Natural To Artificial Neural Computation
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Author :
language : en
Publisher:
Release Date : 1995
From Natural To Artificial Neural Computation written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Neural networks (Computer science) categories.
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
Artificial Neural Networks
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2023-06-21
Artificial Neural Networks written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-21 with Computers categories.
What Is Artificial Neural Networks Computing systems that are inspired by the biological neural networks that make up animal brains are called artificial neural networks (ANNs). These systems are more commonly referred to as neural networks (NNs) or neural nets. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Artificial neural network Chapter 2: Artificial neuron Chapter 3: Unsupervised learning Chapter 4: Backpropagation Chapter 5: Types of artificial neural networks Chapter 6: Deep learning Chapter 7: Convolutional neural network Chapter 8: Long short-term memory Chapter 9: Recurrent neural network Chapter 10: History of artificial neural networks (II) Answering the public top questions about artificial neural networks. (III) Real world examples for the usage of artificial neural networks in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of artificial neural networks. What Is Artificial Intelligence Series The Artificial Intelligence eBook series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The Artificial Intelligence eBook series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.
Trends In Neural Computation
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Author : Ke Chen
language : en
Publisher: Springer
Release Date : 2006-11-15
Trends In Neural Computation written by Ke Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-15 with Computers categories.
Trends in Neural Computation includes twenty chapters contributed by leading experts or formed by extending well-selected papers presented in the 2005 International Conference on Natural Computation. The book reviews the latest progress in a range of different areas of neural computation, including theoretical neural computation, biologically plausible neural modeling, computational cognitive science, artificial neural networks – architectures and learning algorithms and their applications in real-world problems.
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.
Artificial Neural Networks For Computer Vision
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Author : Yi-Tong Zhou
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Artificial Neural Networks For Computer Vision written by Yi-Tong Zhou 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.
This monograph is an outgrowth of the authors' recent research on the de velopment of algorithms for several low-level vision problems using artificial neural networks. Specific problems considered are static and motion stereo, computation of optical flow, and deblurring an image. From a mathematical point of view, these inverse problems are ill-posed according to Hadamard. Researchers in computer vision have taken the "regularization" approach to these problems, where one comes up with an appropriate energy or cost function and finds a minimum. Additional constraints such as smoothness, integrability of surfaces, and preservation of discontinuities are added to the cost function explicitly or implicitly. Depending on the nature of the inver sion to be performed and the constraints, the cost function could exhibit several minima. Optimization of such nonconvex functions can be quite involved. Although progress has been made in making techniques such as simulated annealing computationally more reasonable, it is our view that one can often find satisfactory solutions using deterministic optimization algorithms.
Combining Artificial Neural Nets
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Author : Amanda J.C. Sharkey
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Combining Artificial Neural Nets written by Amanda J.C. Sharkey 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.
This volume, written by leading researchers, presents methods of combining neural nets to improve their performance. The techniques include ensemble-based approaches, where a variety of methods are used to create a set of different nets trained on the same task, and modular approaches, where a task is decomposed into simpler problems. The techniques are also accompanied by an evaluation of their relative effectiveness and their application to a variety of problems.
Advanced Methods In Neural Computing
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Author : Philip D. Wasserman
language : en
Publisher: Van Nostrand Reinhold Company
Release Date : 1993
Advanced Methods In Neural Computing written by Philip D. Wasserman and has been published by Van Nostrand Reinhold Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Computers categories.
This is the engineer's guide to artificial neural networks, the advanced computing innovation which is posed to sweep into the world of business and industry. The author presents the basic principles and advanced concepts by means of high-performance paradigms which function effectively in real-world situations.
