Download or read book Silicon Implementation of Pulse Coded Neural Networks written by Mona E. Zaghloul and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Implementation of Pulse coded Neural Network Applications Using a CMOS Neuron written by Konduri Sai Ramesh Janardana Rao and published by . This book was released on 2004 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Neural Network Analysis Architectures and Applications written by A Browne and published by CRC Press. This book was released on 1997-01-01 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Pulsed Neural Networks written by Wolfgang Maass and published by MIT Press. This book was released on 2001-01-26 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Neuromorphic Systems Engineering written by Tor Sverre Lande and published by Springer. This book was released on 2007-08-26 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Learning on Silicon written by G. Cauwenberghs and published by Springer Science & Business Media. This book was released on 1999-06-30 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Pulse coded Neural Network Implementation in Vlsi written by Yin Hao Liew and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book VLSI Compatible Implementations for Artificial Neural Networks written by Sied Mehdi Fakhraie and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book WCNN 96 San Diego California U S A written by International Neural Network Society and published by Psychology Press. This book was released on 1996 with total page 1408 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Neural Information Processing Systems 12 written by Sara A. Solla and published by MIT Press. This book was released on 2000 with total page 1124 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Graphene for Post Moore Silicon Optoelectronics written by Yang Xu and published by John Wiley & Sons. This book was released on 2023-04-03 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book World Congress on Neural Networks written by Paul Werbos and published by Routledge. This book was released on 2021-09-09 with total page 860 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Neuromorphic Systems Engineering Silicon From Neurobiology written by Alister Hamilton and published by World Scientific. This book was released on 1998-05-13 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuromorphic systems are implementations in silicon of sensory and neural systems whose architecture and design are based on neurobiology. This growing area offers exciting possibilities, such as sensory systems that can compete with human senses and pattern recognition systems that can run in real time. It is at the intersection of neurophysiology, computer science and electrical engineering.This book brings together recent developments in Europe and the US, so that researchers in both academia and industry can find out about the state of the art. As well as elementary material on what neuromorphic systems are and why they are growing in importance, the book contains details of current work. There are articles on aspects of implementing sensory neuromorphic systems, and also on neuromorphic hardware.
Download or read book Innovations in Computer Vision and Data Classification written by Arfan Ghani and published by Springer Nature. This book was released on with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forgetful Logic and Its Applications in the VLSI Implementation of Pulse coded Neural Networks written by Anindya Bhattacharya and published by . This book was released on 2004 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hardware Evolution written by Adrian Thompson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolution through natural selection has been going on for a very long time. Evolution through artificial selection has been practiced by humans for a large part of our history, in the breeding of plants and livestock. Artificial evolution, where we evolve an artifact through artificial selection, has been around since electronic computers became common: about 30 years. Right from the beginning, people have suggested using artificial evolution to design electronics automatically.l Only recently, though, have suitable re configurable silicon chips become available that make it easy for artificial evolution to work with a real, physical, electronic medium: before them, ex periments had to be done entirely in software simulations. Early research concentrated on the potential applications opened-up by the raw speed ad vantage of dedicated digital hardware over software simulation on a general purpose computer. This book is an attempt to show that there is more to it than that. In fact, a radically new viewpoint is possible, with fascinating consequences. This book was written as a doctoral thesis, submitted in September 1996. As such, it was a rather daring exercise in ruthless brevity. Believing that the contribution I had to make was essentially a simple one, I resisted being drawn into peripheral discussions. In the places where I deliberately drop a subject, this implies neither that it's not interesting, nor that it's not relevant: just that it's not a crucial part of the tale I want to tell here.
Download or read book Applied Intelligent Control of Induction Motor Drives written by Tze Fun Chan and published by John Wiley & Sons. This book was released on 2011-01-19 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: Induction motors are the most important workhorses in industry. They are mostly used as constant-speed drives when fed from a voltage source of fixed frequency. Advent of advanced power electronic converters and powerful digital signal processors, however, has made possible the development of high performance, adjustable speed AC motor drives. This book aims to explore new areas of induction motor control based on artificial intelligence (AI) techniques in order to make the controller less sensitive to parameter changes. Selected AI techniques are applied for different induction motor control strategies. The book presents a practical computer simulation model of the induction motor that could be used for studying various induction motor drive operations. The control strategies explored include expert-system-based acceleration control, hybrid-fuzzy/PI two-stage control, neural-network-based direct self control, and genetic algorithm based extended Kalman filter for rotor speed estimation. There are also chapters on neural-network-based parameter estimation, genetic-algorithm-based optimized random PWM strategy, and experimental investigations. A chapter is provided as a primer for readers to get started with simulation studies on various AI techniques. Presents major artificial intelligence techniques to induction motor drives Uses a practical simulation approach to get interested readers started on drive development Authored by experienced scientists with over 20 years of experience in the field Provides numerous examples and the latest research results Simulation programs available from the book's Companion Website This book will be invaluable to graduate students and research engineers who specialize in electric motor drives, electric vehicles, and electric ship propulsion. Graduate students in intelligent control, applied electric motion, and energy, as well as engineers in industrial electronics, automation, and electrical transportation, will also find this book helpful. Simulation materials available for download at www.wiley.com/go/chanmotor