Parallel Architectures For Artificial Neural Networks
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Parallel Architectures For Artificial Neural Networks
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Author : N. Sundararajan
language : en
Publisher: Wiley-IEEE Computer Society Press
Release Date : 1998-12-14
Parallel Architectures For Artificial Neural Networks written by N. Sundararajan and has been published by Wiley-IEEE Computer Society Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-12-14 with Computers categories.
An excellent reference for neural networks research and application, this book covers the parallel implementation aspects of all major artificial neural network models in a single text. Parallel Architectures for Artificial Neural Networks details implementations on various processor architectures built on different hardware platforms, ranging from large, general purpose parallel computers to custom built MIMD machine. Working experts describe their implementation research including results that are then divided into three sections: The theoretical analysis of parallel implementation schemes on MIMD message passing machines The details of parallel implementation of BP neural networks on general purpose, large, parallel computers Four specific purpose parallel neural computer configuration Aimed at graduate students and researchers working in artificial neural networks and parallel computing this work can be used by graduate level educators to illustrate parallel computing methods for ANN simulation. Practitioners will also find the text an ideal reference tool for lucid mathematical analyses.
Parallel Architectures And Neural Networks Fourth Italian Workshop
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Author : E R Caianiello
language : en
Publisher: World Scientific
Release Date : 1991-11-12
Parallel Architectures And Neural Networks Fourth Italian Workshop written by E R Caianiello and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-11-12 with categories.
Organized and supported by IIASS and other Italian institutions, this Workshop in Vietri sul Mare has now become a permanent annual event. The aim is to foster closer links among all groups and individuals working in Europe in this inter- and multi-disciplinary area. Topics cover models, architectures and applications.
Adaptive And Natural Computing Algorithms
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Author : Andrej Dobnikar
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-03
Adaptive And Natural Computing Algorithms written by Andrej Dobnikar 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 2011-03-03 with Computers categories.
The two-volume set LNCS 6593 and 6594 constitutes the refereed proceedings of the 10th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2010, held in Ljubljana, Slovenia, in April 2010. The 83 revised full papers presented were carefully reviewed and selected from a total of 144 submissions. The first volume includes 42 papers and a plenary lecture and is organized in topical sections on neural networks and evolutionary computation.
Neural Network Parallel Computing
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Author : Yoshiyasu Takefuji
language : en
Publisher: Springer Science & Business Media
Release Date : 1992-01-31
Neural Network Parallel Computing written by Yoshiyasu Takefuji 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 1992-01-31 with Technology & Engineering categories.
Neural Network Parallel Computing is the first book available to the professional market on neural network computing for optimization problems. This introductory book is not only for the novice reader, but for experts in a variety of areas including parallel computing, neural network computing, computer science, communications, graph theory, computer aided design for VLSI circuits, molecular biology, management science, and operations research. The goal of the book is to facilitate an understanding as to the uses of neural network models in real-world applications. Neural Network Parallel Computing presents a major breakthrough in science and a variety of engineering fields. The computational power of neural network computing is demonstrated by solving numerous problems such as N-queen, crossbar switch scheduling, four-coloring and k-colorability, graph planarization and channel routing, RNA secondary structure prediction, knight's tour, spare allocation, sorting and searching, and tiling. Neural Network Parallel Computing is an excellent reference for researchers in all areas covered by the book. Furthermore, the text may be used in a senior or graduate level course on the topic.
Deep Learning And Parallel Computing Environment For Bioengineering Systems
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Author : Arun Kumar Sangaiah
language : en
Publisher: Academic Press
Release Date : 2019-07-26
Deep Learning And Parallel Computing Environment For Bioengineering Systems written by Arun Kumar Sangaiah and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-26 with Technology & Engineering categories.
Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas. - Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems - Illustrates the state-of-the-art and recent developments in the new theories and applications of deep learning approaches applied to parallel computing environment in bioengineering systems - Provides concepts and technologies that are successfully used in the implementation of today's intelligent data-centric critical systems and multi-media Cloud-Big data
Vlsi For Artificial Intelligence And Neural Networks
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Author : Jose G. Delgado-Frias
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Vlsi For Artificial Intelligence And Neural Networks written by Jose G. Delgado-Frias 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 book is an edited selection of the papers presented at the International Workshop on VLSI for Artifidal Intelligence and Neural Networks which was held at the University of Oxford in September 1990. Our thanks go to all the contributors and especially to the programme committee for all their hard work. Thanks are also due to the ACM-SIGARCH, the IEEE Computer Society, and the lEE for publicizing the event and to the University of Oxford and SUNY-Binghamton for their active support. We are particularly grateful to Anna Morris, Maureen Doherty and Laura Duffy for coping with the administrative problems. Jose Delgado-Frias Will Moore April 1991 vii PROLOGUE Artificial intelligence and neural network algorithms/computing have increased in complexity as well as in the number of applications. This in tum has posed a tremendous need for a larger computational power than can be provided by conventional scalar processors which are oriented towards numeric and data manipulations. Due to the artificial intelligence requirements (symbolic manipulation, knowledge representation, non-deterministic computations and dynamic resource allocation) and neural network computing approach (non-programming and learning), a different set of constraints and demands are imposed on the computer architectures for these applications.
World Congress On Neural Networks
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Author : Paul Werbos
language : en
Publisher: Routledge
Release Date : 2021-09-09
World Congress On Neural Networks written by Paul Werbos and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-09 with Psychology categories.
Centered around 20 major topic areas of both theoretical and practical importance, the World Congress on Neural Networks provides its registrants -- from a diverse background encompassing industry, academia, and government -- with the latest research and applications in the neural network field.
Vlsi Compatible Implementations For Artificial Neural Networks
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Author : Sied Mehdi Fakhraie
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Vlsi Compatible Implementations For Artificial Neural Networks written by Sied Mehdi Fakhraie 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 Technology & Engineering categories.
This book introduces several state-of-the-art VLSI implementations of artificial neural networks (ANNs). It reviews various hardware approaches to ANN implementations: analog, digital and pulse-coded. The analog approach is emphasized as the main one taken in the later chapters of the book. The area of VLSI implementation of ANNs has been progressing for the last 15 years, but not at the fast pace originally predicted. Several reasons have contributed to the slow progress, with the main one being that VLSI implementation of ANNs is an interdisciplinaly area where only a few researchers, academics and graduate students are willing to venture. The work of Professors Fakhraie and Smith, presented in this book, is a welcome addition to the state-of-the-art and will greatly benefit researchers and students working in this area. Of particular value is the use of experimental results to backup extensive simulations and in-depth modeling. The introduction of a synapse-MOS device is novel. The book applies the concept to a number of applications and guides the reader through more possible applications for future work. I am confident that the book will benefit a potentially wide readership. M. I. Elmasry University of Waterloo Waterloo, Ontario Canada Preface Neural Networks (NNs), generally defined as parallel networks that employ a large number of simple processing elements to perform computation in a distributed fashion, have attracted a lot of attention in the past fifty years. As the result. many new discoveries have been made.
Artificial Neural Nets And Genetic Algorithms
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Author : Rudolf F. Albrecht
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Artificial Neural Nets And Genetic Algorithms written by Rudolf F. Albrecht 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.
Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the processes themselves, significant new computational techniques have evolved which have found application in a large number of diverse fields. This diversity is reflected in the topics which are the subjects of contributions to this volume. There are contributions reporting theoretical developments in the design of neural networks, and in the management of their learning. In a number of contributions, applications to speech recognition tasks, control of industrial processes as well as to credit scoring, and so on, are reflected. Regarding genetic algorithms, several methodological papers consider how genetic algorithms can be improved using an experimental approach, as well as by hybridizing with other useful techniques such as tabu search. The closely related area of classifier systems also receives a significant amount of coverage, aiming at better ways for their implementation. Further, while there are many contributions which explore ways in which genetic algorithms can be applied to real problems, nearly all involve some understanding of the context in order to apply the genetic algorithm paradigm more successfully. That this can indeed be done is evidenced by the range of applications covered in this volume.
Artificial Neural Networks 2
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Author : I. Aleksander
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Artificial Neural Networks 2 written by I. Aleksander and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Computers categories.
This two-volume proceedings compilation is a selection of research papers presented at the ICANN-92. The scope of the volumes is interdisciplinary, ranging from the minutiae of VLSI hardware, to new discoveries in neurobiology, through to the workings of the human mind. USA and European research is well represented, including not only new thoughts from old masters but also a large number of first-time authors who are ensuring the continued development of the field.