ANALOG VLSI AND NEURAL SYSTEMS

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Analog Vlsi And Neural Systems

Author : Carver Mead
ISBN : UOM:49015000947821
Genre : Computers
File Size : 73.40 MB
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The first book to take VLSI into the analog domain and apply it to biology. It provides solid tools for research in artificial intelligence and neurobiology while illustrating powerful new applications for analog systems.
Category: Computers

Adaptive Analog Vlsi Neural Systems

Author : M. Jabri
ISBN : 9789401105255
Genre : Computers
File Size : 80.47 MB
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amplitude ~---. -----. -----. -----,-----. -----,-,~ VfT:j·" 4. 50 4. 00 3. 50 q . 3. 00 /'\. ~ -'" : ! . 2. 50 ,: \ . . . 1! -. i "'" " 2. 00 1. 50 ··GO··O_O_ ,-. . . . &. , . ; D Q . " . . . / 1. 00 0. 50 0. 00 L. -----1. . ---. . l. -----:-:::''"::-::--::-::-'-:::-::------=--::-'-::-:=---=-=""=_:' 5. 00 10. 00 15. 00 Figure 7. 1 The morphology of ST and VT retrograde 1:1. © 1995 IEEE [Coggins, labri, Flower and Pickard {1995}]. ing to the analog domain. Additionally, the use of differential pair multipliers and current node summing in the network allows a min imum of devices in the network itself and hence associated savings in power and area. However, in the last few decades analog signal processing has been used sparingly due to the effects of device off sets, noise and drift*. The neural network architecture alleviates these problems to a large extent due to the fact that it is both highly parallel and adaptive. The fact that the network is trained to recognize morphologies with the analog circuits in-loop means that the synaptic weights can be adapted to cancel device offsets [Castro, Tam and Holler (1993); Castro and Sweet (1993)]. The impact of local un correlated noise is reduced by the parallelism of * Most fabrication processes have been optimised for digital design techniques which results in poor analog performance.
Category: Computers

Analog Vlsi Implementation Of Neural Systems

Author : Carver Mead
ISBN : 9781461316398
Genre : Technology & Engineering
File Size : 70.29 MB
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This volume contains the proceedings of a workshop on Analog Integrated Neural Systems held May 8, 1989, in connection with the International Symposium on Circuits and Systems. The presentations were chosen to encompass the entire range of topics currently under study in this exciting new discipline. Stringent acceptance requirements were placed on contributions: (1) each description was required to include detailed characterization of a working chip, and (2) each design was not to have been published previously. In several cases, the status of the project was not known until a few weeks before the meeting date. As a result, some of the most recent innovative work in the field was presented. Because this discipline is evolving rapidly, each project is very much a work in progress. Authors were asked to devote considerable attention to the shortcomings of their designs, as well as to the notable successes they achieved. In this way, other workers can now avoid stumbling into the same traps, and evolution can proceed more rapidly (and less painfully). The chapters in this volume are presented in the same order as the corresponding presentations at the workshop. The first two chapters are concerned with fmding solutions to complex optimization problems under a predefmed set of constraints. The first chapter reports what is, to the best of our knowledge, the first neural-chip design. In each case, the physics of the underlying electronic medium is used to represent a cost function in a natural way, using only nearest-neighbor connectivity.
Category: Technology & Engineering

Learning On Silicon

Author : G. Cauwenberghs
ISBN : 0792385551
Genre : Technology & Engineering
File Size : 73.33 MB
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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.
Category: Technology & Engineering

Analog Vlsi

Author : Shih-Chii Liu
ISBN : 0262122553
Genre : Computers
File Size : 53.55 MB
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An introduction to the design of analog VLSI circuits.
Category: Computers

Analog Vlsi Neural Networks

Author : Yoshiyasu Takefuji
ISBN : 9781461535829
Genre : Technology & Engineering
File Size : 60.26 MB
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This book brings together in one place important contributions and state-of-the-art research in the rapidly advancing area of analog VLSI neural networks. The book serves as an excellent reference, providing insights into some of the most important issues in analog VLSI neural networks research efforts.
Category: Technology & Engineering

Analog Vlsi Circuits For The Perception Of Visual Motion

Author : Alan A. Stocker
ISBN : 9780470034880
Genre : Technology & Engineering
File Size : 39.34 MB
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Although it is now possible to integrate many millions of transistors on a single chip, traditional digital circuit technology is now reaching its limits, facing problems of cost and technical efficiency when scaled down to ever-smaller feature sizes. The analysis of biological neural systems, especially for visual processing, has allowed engineers to better understand how complex networks can effectively process large amounts of information, whilst dealing with difficult computational challenges. Analog and parallel processing are key characteristics of biological neural networks. Analog VLSI circuits using the same features can therefore be developed to emulate brain-style processing. Using standard CMOS technology, they can be cheaply manufactured, permitting efficient industrial and consumer applications in robotics and mobile electronics. This book explores the theory, design and implementation of analog VLSI circuits, inspired by visual motion processing in biological neural networks. Using a novel approach pioneered by the author himself, Stocker explains in detail the construction of a series of electronic chips, providing the reader with a valuable practical insight into the technology. Analog VLSI Circuits for the Perception of Visual Motion: analyses the computational problems in visual motion perception; examines the issue of optimization in analog networks through high level processes such as motion segmentation and selective attention; demonstrates network implementation in analog VLSI CMOS technology to provide computationally efficient devices; sets out measurements of final hardware implementation; illustrates the similarities of the presented circuits with the human visual motion perception system; includes an accompanying website with video clips of circuits under real-time visual conditions and additional supplementary material. With a complete review of all existing neuromorphic analog VLSI systems for visual motion sensing, Analog VLSI Circuits for the Perception of Visual Motion is a unique reference for advanced students in electrical engineering, artificial intelligence, robotics and computational neuroscience. It will also be useful for researchers, professionals, and electronics engineers working in the field.
Category: Technology & Engineering

Introduction To Vlsi Systems

Author : Carver Mead
ISBN : 0201043580
Genre : Computers
File Size : 68.43 MB
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MOS devices and circuits. Integrated system fabrication. Data and control flow in systematic structures. Implementing integrated system designs: from circuit topology to patterning geometry to wafer fabrication. Overview of an LSI computer system, and the design of the OM2 data path chip. Architecture and design of system controllers, and the design of the OM2 controller chip. System timing. Highly concurrent systems. Physics of computational systems.
Category: Computers

Neuromorphic Systems Engineering

Author : Tor Sverre Lande
ISBN : 9780585280011
Genre : Technology & Engineering
File Size : 29.69 MB
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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.
Category: Technology & Engineering

Neural Information Processing And Vlsi

Author : Bing J. Sheu
ISBN : 9781461522478
Genre : Technology & Engineering
File Size : 33.10 MB
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Neural Information Processing and VLSI provides a unified treatment of this important subject for use in classrooms, industry, and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analog and digital VLSI parallel processing techniques. Neural Information Processing and VLSI systematically presents various neural network paradigms, computing architectures, and the associated electronic/optical implementations using efficient VLSI design methodologies. Conventional digital machines cannot perform computationally-intensive tasks with satisfactory performance in such areas as intelligent perception, including visual and auditory signal processing, recognition, understanding, and logical reasoning (where the human being and even a small living animal can do a superb job). Recent research advances in artificial and biological neural networks have established an important foundation for high-performance information processing with more efficient use of computing resources. The secret lies in the design optimization at various levels of computing and communication of intelligent machines. Each neural network system consists of massively paralleled and distributed signal processors with every processor performing very simple operations, thus consuming little power. Large computational capabilities of these systems in the range of some hundred giga to several tera operations per second are derived from collectively parallel processing and efficient data routing, through well-structured interconnection networks. Deep-submicron very large-scale integration (VLSI) technologies can integrate tens of millions of transistors in a single silicon chip for complex signal processing and information manipulation. The book is suitable for those interested in efficient neurocomputing as well as those curious about neural network system applications. It has been especially prepared for use as a text for advanced undergraduate and first year graduate students, and is an excellent reference book for researchers and scientists working in the fields covered.
Category: Technology & Engineering