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VLSI Artificial Neural Networks Engineering

Author : Mohamed I. Elmasry

Publisher : Springer Science & Business Media

Page : 335 pages

File Size : 31,30 MB

Release : 2012-12-06

Category : Technology & Engineering

ISBN : 146152766X

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Book Description

Engineers have long been fascinated by how efficient and how fast biological neural networks are capable of performing such complex tasks as recognition. Such networks are capable of recognizing input data from any of the five senses with the necessary accuracy and speed to allow living creatures to survive. Machines which perform such complex tasks as recognition, with similar ac curacy and speed, were difficult to implement until the technological advances of VLSI circuits and systems in the late 1980's. Since then, the field of VLSI Artificial Neural Networks (ANNs) have witnessed an exponential growth and a new engineering discipline was born. Today, many engineering curriculums have included a course or more on the subject at the graduate or senior under graduate levels. Since the pioneering book by Carver Mead; "Analog VLSI and Neural Sys tems", Addison-Wesley, 1989; there were a number of excellent text and ref erence books on the subject, each dealing with one or two topics. This book attempts to present an integrated approach of a single research team to VLSI ANNs Engineering.



VLSI for Artificial Intelligence and Neural Networks

Author : Jose G. Delgado-Frias

Publisher : Springer Science & Business Media

Page : 411 pages

File Size : 41,13 MB

Release : 2012-12-06

Category : Computers

ISBN : 1461537525

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Book Description

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.



Neural Information Processing and VLSI

Author : Bing J. Sheu

Publisher : Springer Science & Business Media

Page : 569 pages

File Size : 44,72 MB

Release : 2012-12-06

Category : Technology & Engineering

ISBN : 1461522471

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Book Description

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.



Engineering Applications of Bio-Inspired Artificial Neural Networks

Author : Jose Mira

Publisher : Springer Science & Business Media

Page : 942 pages

File Size : 48,19 MB

Release : 1999-05-19

Category : Computers

ISBN : 9783540660682

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Book Description

This book constitutes, together with its compagnion LNCS 1606, the refereed proceedings of the International Work-Conference on Artificial and Neural Networks, IWANN'99, held in Alicante, Spain in June 1999. The 91 revised papers presented were carefully reviewed and selected for inclusion in the book. This volume is devoted to applications of biologically inspired artificial neural networks in various engineering disciplines. The papers are organized in parts on artificial neural nets simulation and implementation, image processing, and engineering applications.



Analog VHDL

Author : Andrzej T. Rosinski

Publisher : Springer Science & Business Media

Page : 110 pages

File Size : 35,77 MB

Release : 2012-12-06

Category : Technology & Engineering

ISBN : 1461557534

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Book Description

Analog VHDL brings together in one place important contributions and up-to-date research results in this fast moving area. Analog VHDL serves as an excellent reference, providing insight into some of the most challenging research issues in the field.



Analog VLSI and Neural Systems

Author : Carver Mead

Publisher : Addison Wesley Publishing Company

Page : 416 pages

File Size : 49,62 MB

Release : 1989

Category : Computers

ISBN :

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Book Description

A self-contained text, suitable for a broad audience. Presents basic concepts in electronics, transistor physics, and neurobiology for readers without backgrounds in those areas. Annotation copyrighted by Book News, Inc., Portland, OR



VLSI and Hardware Implementations using Modern Machine Learning Methods

Author : Sandeep Saini

Publisher : CRC Press

Page : 329 pages

File Size : 49,85 MB

Release : 2021-12-30

Category : Technology & Engineering

ISBN : 1000523810

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Book Description

Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.



Advanced Circuits and Systems for Healthcare and Security Applications

Author : Balwinder Raj

Publisher : CRC Press

Page : 269 pages

File Size : 30,91 MB

Release : 2022-09-08

Category : Computers

ISBN : 1000652823

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Book Description

VLSI devices downscaling is a very significant part of the design to improve the performance of VLSI industry outcomes, which results in high speed and low power of operation of integrated devices. The increasing use of VLSI circuits dealing with highly sensitive information, such as healthcare information, means adequate security measures are required to be taken for the secure storage and transmission. Advanced Circuits and Systems for Healthcare and Security Applications provides broader coverage of the basic aspects of advanced circuits and security and introduces the corresponding principles. By the end of this book, you will be familiarized with the theoretical frameworks, technical methodologies, and empirical research findings in the field to protect your computers and information from adversaries. Advanced circuits and the comprehensive material of this book will keep you interested and involved throughout. The book is an integrated source which aims at understanding the basic concepts associated with the security of the advanced circuits and the cyber world as a first step towards achieving high-end protection from adversaries and hackers. The content includes theoretical frameworks and recent empirical findings in the field to understand the associated principles, key challenges and recent real-time applications of the advanced circuits and cybersecurity. It illustrates the notions, models, and terminologies that are widely used in the area of circuits and security, identifies the existing security issues in the field, and evaluates the underlying factors that influence the security of the systems. It emphasizes the idea of understanding the motivation of the attackers to establish adequate security measures and to mitigate security attacks in a better way. This book also outlines the exciting areas of future research where the already-existing methodologies can be implemented. Moreover, this book is suitable for students, researchers, and professionals in the who are looking forward to carry out research in the field of advanced circuits and systems for healthcare and security applications; faculty members across universities; and software developers.



Neuromorphic Systems Engineering

Author : Tor Sverre Lande

Publisher : Springer Science & Business Media

Page : 462 pages

File Size : 13,79 MB

Release : 1998-04-30

Category : Technology & Engineering

ISBN : 0792381580

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Book Description

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.



Analog VLSI Implementation of Neural Systems

Author : Carver Mead

Publisher : Springer Science & Business Media

Page : 250 pages

File Size : 47,46 MB

Release : 2012-12-06

Category : Technology & Engineering

ISBN : 1461316391

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Book Description

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.