Parallel Architectures For Artificial Neural Networks

Author : N. Sundararajan,P. Saratchandran
Publisher : Wiley-IEEE Computer Society Press
Page : 424 pages
File Size : 43,5 Mb
Release : 1998-12-14
Category : Computers
ISBN : UOM:39015046908375

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Parallel Architectures for Artificial Neural Networks by N. Sundararajan,P. Saratchandran Pdf

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.

Author : E R Caianiello
Publisher : World Scientific
Page : 396 pages
File Size : 53,7 Mb
Release : 1991-11-12
Category : Electronic
ISBN : 9789814555784

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Parallel Architectures And Neural Networks: Fourth Italian Workshop by E R Caianiello Pdf

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.

Author : E R Caianiello
Publisher : World Scientific
Page : 440 pages
File Size : 51,8 Mb
Release : 1990-12-13
Category : Computers
ISBN : 9789814611350

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Parallel Architectures And Neural Networks - Third Italian Workshop by E R Caianiello Pdf

Author : Eduardo R. Caianiello
Publisher : Unknown
Page : 388 pages
File Size : 41,6 Mb
Release : 1990
Category : Medical
ISBN : UOM:39015018973001

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Parallel Architectures and Neural Networks by Eduardo R. Caianiello Pdf

Author : Rolf Eckmiller,Georg Hartmann,Gert Hauske
Publisher : North Holland
Page : 652 pages
File Size : 42,7 Mb
Release : 1990
Category : Computers
ISBN : UOM:39015017921100

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Parallel Processing in Neural Systems and Computers by Rolf Eckmiller,Georg Hartmann,Gert Hauske Pdf

The 119 contributions in this book cover a range of topics, including parallel computing, parallel processing in biological neural systems, simulators for artificial neural networks, neural networks for visual and auditory pattern recognition as well as for motor control, AI, and examples of optical and molecular computing. The book may be regarded as a state-of-the-art report and at the same time as an Interdisciplinary Reference Source' for parallel processing. It should catalyze international and interdisciplinary cooperation among computer scientists, neuroscientists, physicists and engineers in the attempt to: 1) decipher parallel information processes in biology, physics and chemistry 2) design conceptually similar technical parallel information processors."

Author : J. Geller,H. Kitano,C.B. Suttner
Publisher : Elsevier
Page : 357 pages
File Size : 52,9 Mb
Release : 1997-02-10
Category : Computers
ISBN : 9780080553825

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Parallel Processing for Artificial Intelligence 3 by J. Geller,H. Kitano,C.B. Suttner Pdf

The third in an informal series of books about parallel processing for Artificial Intelligence, this volume is based on the assumption that the computational demands of many AI tasks can be better served by parallel architectures than by the currently popular workstations. However, no assumption is made about the kind of parallelism to be used. Transputers, Connection Machines, farms of workstations, Cellular Neural Networks, Crays, and other hardware paradigms of parallelism are used by the authors of this collection. The papers arise from the areas of parallel knowledge representation, neural modeling, parallel non-monotonic reasoning, search and partitioning, constraint satisfaction, theorem proving, parallel decision trees, parallel programming languages and low-level computer vision. The final paper is an experience report about applications of massive parallelism which can be said to capture the spirit of a whole period of computing history. This volume provides the reader with a snapshot of the state of the art in Parallel Processing for Artificial Intelligence.

Author : Andrej Dobnikar,Uroš Lotric,Branko Šter
Publisher : Springer
Page : 433 pages
File Size : 40,6 Mb
Release : 2011-04-09
Category : Computers
ISBN : 9783642202827

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Adaptive and Natural Computing Algorithms by Andrej Dobnikar,Uroš Lotric,Branko Šter Pdf

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.

Author : Qutaibah M. Malluhi
Publisher : Unknown
Page : 256 pages
File Size : 47,6 Mb
Release : 1994
Category : Neural networks (Computer science)
ISBN : OCLC:30952272

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Mapping Artificial Neural Networks on Massively Parallel Architectures by Qutaibah M. Malluhi Pdf

Author : J. Smith
Publisher : Createspace Independent Publishing Platform
Page : 0 pages
File Size : 50,7 Mb
Release : 2017-02-26
Category : Computer architecture
ISBN : 1544133316

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Neural Network Architectures. Examples Using MATLAB by J. Smith Pdf

MATLAB has the tool Neural Network Toolbox that provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control. The toolbox includes convolutional neural network and autoencoder deep learning algorithms for image classification and feature learning tasks. To speed up training of large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox. The more important features are the following: - Deep learning, including convolutional neural networks and autoencoders - Parallel computing and GPU support for accelerating training (with Parallel Computing Toolbox) - Supervised learning algorithms, including multilayer, radial basis, learning vector quantization (LVQ), time-delay, nonlinear autoregressive (NARX), and recurrent neural network (RNN) - Unsupervised learning algorithms, including self-organizing maps and competitive layers - Apps for data-fitting, pattern recognition, and clustering - Preprocessing, postprocessing, and network visualization for improving training efficiency and assessing network performance - Simulink(R) blocks for building and evaluating neural networks and for control systems applications Neural networks are composed of simple elements operating in parallel. These elements are inspired by biological nervous systems. As in nature, the connections between elements largely determine the network function. You can train a neural network to perform a particular function by adjusting the values of the connections (weights) between elements.

Author : Yoshiyasu Takefuji
Publisher : Springer Science & Business Media
Page : 237 pages
File Size : 55,6 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461536420

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Neural Network Parallel Computing by Yoshiyasu Takefuji Pdf

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.

Author : Arun Kumar Sangaiah
Publisher : Academic Press
Page : 280 pages
File Size : 54,9 Mb
Release : 2019-07-26
Category : Computers
ISBN : 9780128172933

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Deep Learning and Parallel Computing Environment for Bioengineering Systems by Arun Kumar Sangaiah Pdf

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

Author : Craig W. Rizzo
Publisher : Unknown
Page : 77 pages
File Size : 46,9 Mb
Release : 1998-03-01
Category : Neural networks (Computer science)
ISBN : 142356278X

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Parallel Implementation of an Artificial Neural Network Integrated Feature and Architecture Selection Algorithm by Craig W. Rizzo Pdf

The selection of salient features and an appropriate hidden layer architecture contributes significantly to the performance of a neural network. A number of metrics and methodologies exist for estimating these parameters. This research builds on recent efforts to integrate feature and architecture selection for the multilayer perceptron. In the first stage of work a current algorithm is developed in a parallel environment, significantly improving its efficiency and utility. In the second stage, improvements to the algorithm are proposed. With regards to feature selection, a common random number (CRN) addition is proposed. Two new methods of architecture selection are examined, to include an information criterion and a signal to noise based procedure. These methodologies are shown to improve algorithm performance.

Author : Emile H.L. Aarts,Jan van Leeuwen,Martin Rem
Publisher : Springer
Page : 942 pages
File Size : 47,8 Mb
Release : 2013-11-11
Category : Computers
ISBN : 9783662252093

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Parle ’91 Parallel Architectures and Languages Europe by Emile H.L. Aarts,Jan van Leeuwen,Martin Rem Pdf

The innovative progress in the development oflarge-and small-scale parallel computing systems and their increasing availability have caused a sharp rise in interest in the scientific principles that underlie parallel computation and parallel programming. The biannual "Parallel Architectures and Languages Europe" (PARLE) conferences aim at presenting current research material on all aspects of the theory, design, and application of parallel computing systems and parallel processing. At the same time, the goal of the PARLE conferences is to provide a forum for researchers and practitioners to ex change ideas on recent developments and trends in the field of parallel com puting and parallel programming. The first ~wo conferences, PARLE '87 and PARLE '89, have succeeded in meeting this goal and made PARLE a conference that is recognized worldwide in the field of parallel computation. PARLE '91 again offers a wealth of high-quality research material for the benefit of the scientific community. Compared to its predecessors, the scope of PARLE '91 has been broadened so as to cover the area of parallel algo rithms and complexity, in addition to the central themes of parallel archi tectures and languages. The proceedings of the PARLE '91 conference contain the text of all con tributed papers that were selected for the programme and of the invited papers by leading experts in the field.

Author : Paul Werbos,Harold Szu,Bernard Widrow
Publisher : Routledge
Page : 860 pages
File Size : 50,6 Mb
Release : 2021-09-09
Category : Psychology
ISBN : 9781317713425

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World Congress on Neural Networks by Paul Werbos,Harold Szu,Bernard Widrow Pdf

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.

Author : Albert Chun-Chen Liu,Oscar Ming Kin Law
Publisher : John Wiley & Sons
Page : 244 pages
File Size : 53,8 Mb
Release : 2021-08-31
Category : Computers
ISBN : 9781119810452

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Artificial Intelligence Hardware Design by Albert Chun-Chen Liu,Oscar Ming Kin Law Pdf

ARTIFICIAL INTELLIGENCE HARDWARE DESIGN Learn foundational and advanced topics in Neural Processing Unit design with real-world examples from leading voices in the field In Artificial Intelligence Hardware Design: Challenges and Solutions, distinguished researchers and authors Drs. Albert Chun Chen Liu and Oscar Ming Kin Law deliver a rigorous and practical treatment of the design applications of specific circuits and systems for accelerating neural network processing. Beginning with a discussion and explanation of neural networks and their developmental history, the book goes on to describe parallel architectures, streaming graphs for massive parallel computation, and convolution optimization. The authors offer readers an illustration of in-memory computation through Georgia Tech’s Neurocube and Stanford’s Tetris accelerator using the Hybrid Memory Cube, as well as near-memory architecture through the embedded eDRAM of the Institute of Computing Technology, the Chinese Academy of Science, and other institutions. Readers will also find a discussion of 3D neural processing techniques to support multiple layer neural networks, as well as information like: A thorough introduction to neural networks and neural network development history, as well as Convolutional Neural Network (CNN) models Explorations of various parallel architectures, including the Intel CPU, Nvidia GPU, Google TPU, and Microsoft NPU, emphasizing hardware and software integration for performance improvement Discussions of streaming graph for massive parallel computation with the Blaize GSP and Graphcore IPU An examination of how to optimize convolution with UCLA Deep Convolutional Neural Network accelerator filter decomposition Perfect for hardware and software engineers and firmware developers, Artificial Intelligence Hardware Design is an indispensable resource for anyone working with Neural Processing Units in either a hardware or software capacity.