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Silicon Implementation of Pulse Coded Neural Networks

Author: Mona E. Zaghloul

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 293

ISBN-13: 1461526809

When confronted with the hows and whys of nature's computational engines, some prefer to focus upon neural function: addressing issues of neural system behavior and its relation to natural intelligence. Then there are those who prefer the study of the "mechanics" of neural systems: the nuts and bolts of the "wetware": the neurons and synapses. Those who investigate pulse coded implementations ofartificial neural networks know what it means to stand at the boundary which lies between these two worlds: not just asking why natural neural systems behave as they do, but also how they achieve their marvelous feats. The research results presented in this book not only address more conventional abstract notions of neural-like processing, but also the more specific details ofneural-like processors. It has been established for some time that natural neural systems perform a great deal of information processing via electrochemical pulses. Accordingly, pulse coded neural network concepts are receiving increased attention in artificial neural network research. This increased interest is compounded by continuing advances in the field of VLSI circuit design. This is the first time in history in which it is practical to construct networks of neuron-like circuits of reasonable complexity that can be applied to real problems. We believe that the pioneering work in artificial neural systems presented in this book will lead to further advances that will not only be useful in some practical sense, but may also provide some additional insight into the operation of their natural counterparts.

Neural Network Analysis, Architectures and Applications

Author: A Browne

Publisher: CRC Press

Published: 1997-01-01

Total Pages: 294

ISBN-13: 9780750304993

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Neural Network Analysis, Architectures and Applications discusses the main areas of neural networks, with each authoritative chapter covering the latest information from different perspectives. Divided into three parts, the book first lays the groundwork for understanding and simplifying networks. It then describes novel architectures and algorithms, including pulse-stream techniques, cellular neural networks, and multiversion neural computing. The book concludes by examining various neural network applications, such as neuron-fuzzy control systems and image compression. This final part of the book also provides a case study involving oil spill detection. This book is invaluable for students and practitioners who have a basic understanding of neural computing yet want to broaden and deepen their knowledge of the field.

Pulsed Neural Networks

Author: Wolfgang Maass

Publisher: MIT Press

Published: 2001-01-26

Total Pages: 414

ISBN-13: 9780262632218

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Most practical applications of artificial neural networks are based on a computational model involving the propagation of continuous variables from one processing unit to the next. In recent years, data from neurobiological experiments have made it increasingly clear that biological neural networks, which communicate through pulses, use the timing of the pulses to transmit information and perform computation. This realization has stimulated significant research on pulsed neural networks, including theoretical analyses and model development, neurobiological modeling, and hardware implementation. This book presents the complete spectrum of current research in pulsed neural networks and includes the most important work from many of the key scientists in the field. Terrence J. Sejnowski's foreword, "Neural Pulse Coding," presents an overview of the topic. The first half of the book consists of longer tutorial articles spanning neurobiology, theory, algorithms, and hardware. The second half contains a larger number of shorter research chapters that present more advanced concepts. The contributors use consistent notation and terminology throughout the book. Contributors Peter S. Burge, Stephen R. Deiss, Rodney J. Douglas, John G. Elias, Wulfram Gerstner, Alister Hamilton, David Horn, Axel Jahnke, Richard Kempter, Wolfgang Maass, Alessandro Mortara, Alan F. Murray, David P. M. Northmore, Irit Opher, Kostas A. Papathanasiou, Michael Recce, Barry J. P. Rising, Ulrich Roth, Tim Schönauer, Terrence J. Sejnowski, John Shawe-Taylor, Max R. van Daalen, J. Leo van Hemmen, Philippe Venier, Hermann Wagner, Adrian M. Whatley, Anthony M. Zador

Neuromorphic Systems Engineering

Author: Tor Sverre Lande

Publisher: Springer

Published: 2007-08-26

Total Pages: 462

ISBN-13: 0585280010

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Neuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological neural systems, which are used as inspiration for building large electronic systems in silicon. By adequate engineering, these silicon systems are made useful to mankind. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the reader with a snapshot of neuromorphic engineering today. It is organized into five parts viewing state-of-the-art developments within neuromorphic engineering from different perspectives. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the first collection of neuromorphic systems descriptions with firm foundations in silicon. Topics presented include: large scale analog systems in silicon neuromorphic silicon auditory (ear) and vision (eye) systems in silicon learning and adaptation in silicon merging biology and technology micropower analog circuit design analog memory analog interchipcommunication on digital buses £/LIST£ Neuromorphic Systems Engineering: Neural Networks in Silicon serves as an excellent resource for scientists, researchers and engineers in this emerging field, and may also be used as a text for advanced courses on the subject.

Learning on Silicon

Author: G. Cauwenberghs

Publisher: Springer Science & Business Media

Published: 1999-06-30

Total Pages: 444

ISBN-13: 9780792385554

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Learning on Silicon combines models of adaptive information processing in the brain with advances in microelectronics technology and circuit design. The premise is to construct integrated systems not only loaded with sufficient computational power to handle demanding signal processing tasks in sensory perception and pattern recognition, but also capable of operating autonomously and robustly in unpredictable environments through mechanisms of adaptation and learning. This edited volume covers the spectrum of Learning on Silicon in five parts: adaptive sensory systems, neuromorphic learning, learning architectures, learning dynamics, and learning systems. The 18 chapters are documented with examples of fabricated systems, experimental results from silicon, and integrated applications ranging from adaptive optics to biomedical instrumentation. As the first comprehensive treatment on the subject, Learning on Silicon serves as a reference for beginners and experienced researchers alike. It provides excellent material for an advanced course, and a source of inspiration for continued research towards building intelligent adaptive machines.

VLSI — Compatible Implementations for Artificial Neural Networks

Author: Sied Mehdi Fakhraie

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 216

ISBN-13: 1461563119

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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.

WCNN'96, San Diego, California, U.S.A.

Author: International Neural Network Society

Publisher: Psychology Press

Published: 1996

Total Pages: 1408

ISBN-13: 9780805826081

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Advances in Neural Information Processing Systems 12

Author: Sara A. Solla

Publisher: MIT Press

Published: 2000

Total Pages: 1124

ISBN-13: 9780262194501

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The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.

Graphene for Post-Moore Silicon Optoelectronics

Author: Yang Xu

Publisher: John Wiley & Sons

Published: 2023-04-03

Total Pages: 197

ISBN-13: 3527351817

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Provides timely coverage of an important research area that is highly relevant to advanced detection and control technology Projecting device performance beyond the scaling limits of Moore’s law requires technologies based on novel materials and device architecture. Due to its excellent electronic, thermal, and optical properties, graphene has emerged as a scalable, low-cost material with enormous integration possibilities for numerous optoelectronic applications. Graphene for Post-Moore Silicon Optoelectronics presents an up-to-date overview of the fundamentals, applications, challenges, and opportunities of integrating graphene and other 2D materials with silicon (Si) technologies. With an emphasis on graphene-silicon (Gr/Si) integrated devices in optoelectronics, this valuable resource also addresses emerging applications such as optoelectronic synaptic devices, optical modulators, and infrared image sensors. The book opens with an introduction to graphene for silicon optoelectronics, followed by chapters describing the growth, transfer, and physics of graphene/silicon junctions. Subsequent chapters each focus on a particular Gr/Si application, including high-performance photodetectors, solar energy harvesting devices, and hybrid waveguide devices. The book concludes by offering perspectives on the future challenges and prospects of Gr/Si optoelectronics, including the emergence of wafer-scale systems and neuromorphic optoelectronics. Illustrates the benefits of graphene-based electronics and hybrid device architectures that incorporate existing Si technology Covers all essential aspects of Gr/Si devices, including material synthesis, device fabrication, system integration, and related physics Summarizes current progress and future challenges of wafer-scale 2D-Si integrated optoelectronic devices Explores a wide range of Gr/Si devices, such as synaptic phototransistors, hybrid waveguide modulators, and graphene thermopile image sensors Graphene for Post-Moore Silicon Optoelectronics is essential reading for materials scientists, electronics engineers, and chemists in both academia and industry working with the next generation of Gr/Si devices.

World Congress on Neural Networks

Author: Paul Werbos

Publisher: Routledge

Published: 2021-09-09

Total Pages: 860

ISBN-13: 1317713427

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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.