Neural Networks Theory
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Neural Networks Theory
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Author : Alexander I. Galushkin
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-29
Neural Networks Theory written by Alexander I. Galushkin 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 2007-10-29 with Technology & Engineering categories.
This book, written by a leader in neural network theory in Russia, uses mathematical methods in combination with complexity theory, nonlinear dynamics and optimization. It details more than 40 years of Soviet and Russian neural network research and presents a systematized methodology of neural networks synthesis. The theory is expansive: covering not just traditional topics such as network architecture but also neural continua in function spaces as well.
Fuzzy Neural Network Theory And Application
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Author : Puyin Liu
language : en
Publisher: World Scientific
Release Date : 2004
Fuzzy Neural Network Theory And Application written by Puyin Liu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to help the reader grasp the underlying theory. This is a valuable reference for scientists and engineers working in mathematics, computer science, control or other fields related to information processing. It can also be used as a textbook for graduate courses in applied mathematics, computer science, automatic control and electrical engineering.
Process Neural Networks
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Author : Xingui He
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-05
Process Neural Networks written by Xingui He 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 2010-07-05 with Computers categories.
"Process Neural Network: Theory and Applications" proposes the concept and model of a process neural network for the first time, showing how it expands the mapping relationship between the input and output of traditional neural networks and enhances the expression capability for practical problems, with broad applicability to solving problems relating to processes in practice. Some theoretical problems such as continuity, functional approximation capability, and computing capability, are closely examined. The application methods, network construction principles, and optimization algorithms of process neural networks in practical fields, such as nonlinear time-varying system modeling, process signal pattern recognition, dynamic system identification, and process forecast, are discussed in detail. The information processing flow and the mapping relationship between inputs and outputs of process neural networks are richly illustrated. Xingui He is a member of Chinese Academy of Engineering and also a professor at the School of Electronic Engineering and Computer Science, Peking University, China, where Shaohua Xu also serves as a professor.
Introduction To Neural Networks
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Author : Jeannette Lawrence
language : en
Publisher:
Release Date : 1994
Introduction To Neural Networks written by Jeannette Lawrence and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.
Artificial Neural Networks
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Author : Dan W. Patterson
language : en
Publisher:
Release Date : 1996
Artificial Neural Networks written by Dan W. Patterson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.
This comprehensive tutorial on artifical neural networks covers all the important neural network architectures as well as the most recent theory--e.g., pattern recognition, statistical theory, and other mathematical prerequisites. A broad range of applications is provided for each of the architectures.
Complex Valued Neural Networks Theories And Applications
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Author : Akira Hirose
language : en
Publisher: World Scientific
Release Date : 2003-11-18
Complex Valued Neural Networks Theories And Applications written by Akira Hirose and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-11-18 with Computers categories.
In recent years, complex-valued neural networks have widened the scope of application in optoelectronics, imaging, remote sensing, quantum neural devices and systems, spatiotemporal analysis of physiological neural systems, and artificial neural information processing. In this first-ever book on complex-valued neural networks, the most active scientists at the forefront of the field describe theories and applications from various points of view to provide academic and industrial researchers with a comprehensive understanding of the fundamentals, features and prospects of the powerful complex-valued networks.
Theoretical Mechanics Of Biological Neural Networks
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Author : Ronald J. MacGregor
language : en
Publisher: Elsevier
Release Date : 2012-12-02
Theoretical Mechanics Of Biological Neural Networks written by Ronald J. MacGregor and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-02 with Science categories.
Theoretical Mechanics of Biological Neural Networks presents an extensive and coherent discusson and formulation of the generation and integration of neuroelectric signals in single neurons. The approach relates computer simulation programs for neurons of arbitrary complexity to fundamental gating processes of transmembrance ionic fluxes of synapses of excitable membranes. Listings of representative computer programs simulating arbitrary neurons, and local and composite neural networks are included. - Develops a theory of dynamic similarity for characterising the firing rate sensitivites of neurons in terms of their characteristic anatomical and physiological parameters - Presents the sequential configuration theory - a theoretical presentation of coordinated firing patterns in entire neural population - Presents the outlines of mechanics for multiple interacting networks in composite systems
Advances In Neural Networks Computational And Theoretical Issues
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Author : Simone Bassis
language : en
Publisher: Springer
Release Date : 2015-06-05
Advances In Neural Networks Computational And Theoretical Issues written by Simone Bassis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-05 with Technology & Engineering categories.
This book collects research works that exploit neural networks and machine learning techniques from a multidisciplinary perspective. Subjects covered include theoretical, methodological and computational topics which are grouped together into chapters devoted to the discussion of novelties and innovations related to the field of Artificial Neural Networks as well as the use of neural networks for applications, pattern recognition, signal processing, and special topics such as the detection and recognition of multimodal emotional expressions and daily cognitive functions, and bio-inspired memristor-based networks. Providing insights into the latest research interest from a pool of international experts coming from different research fields, the volume becomes valuable to all those with any interest in a holistic approach to implement believable, autonomous, adaptive and context-aware Information Communication Technologies.
Neural Networks
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Author : Berndt Müller
language : en
Publisher: Springer Science & Business Media
Release Date : 1995-10-02
Neural Networks written by Berndt Müller 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 1995-10-02 with Computers categories.
Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.
Neural Theories Of Mind
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Author : William R. Uttal
language : en
Publisher: Psychology Press
Release Date : 2020-07-24
Neural Theories Of Mind written by William R. Uttal and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-24 with Psychology categories.
In this fascinating book, William R. Uttal raises the possibility that, however much we learn about the anatomy and physiology of the brain and psychology, we may never be able to cross the final bridge explaining how the mind is produced by the brain. Three main classes of mind-brain theory are considered and rejected: field theories, because they are based on a superficial analogy; single cell theories, because they emerge from a massive uncontrolled experimental program; and neural net theories, because they are constrained by combinatorial complexity. To support his argument, Uttal explores the empirical and conceptual foundations of these theoretical approaches and identifies flaws in their fundamental logic. The author concludes that the problems preventing solution of the mind-brain problem are intractable, yet well within the confines of natural science.