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Analog Vlsi Implementation Of Neural Systems
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Book Synopsis Analog VLSI Implementation of Neural Systems by : Carver Mead
Download or read book Analog VLSI Implementation of Neural Systems written by Carver Mead and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Adaptive Analog VLSI Neural Systems by : M. Jabri
Download or read book Adaptive Analog VLSI Neural Systems written by M. Jabri and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Analog VLSI Neural Systems is the first practical book on neural networks learning chips and systems. It covers the entire process of implementing neural networks in VLSI chips, beginning with the crucial issues of learning algorithms in an analog framework and limited precision effects, and giving actual case studies of working systems. The approach is systems and applications oriented throughout, demonstrating the attractiveness of such an approach for applications such as adaptive pattern recognition and optical character recognition. Dr Jabri and his co-authors from AT&T Bell Laboratories, Bellcore and the University of Sydney provide a comprehensive introduction to VLSI neural networks suitable for research and development staff and advanced students.
Book Synopsis Analog VLSI and Neural Systems by : Carver Mead
Download or read book Analog VLSI and Neural Systems written by Carver Mead and published by Addison Wesley Publishing Company. This book was released on 1989 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Analog VLSI Neural Networks by : Yoshiyasu Takefuji
Download or read book Analog VLSI Neural Networks written by Yoshiyasu Takefuji and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author :Jose G. Delgado-Frias Publisher :Springer Science & Business Media ISBN 13 :1489913319 Total Pages :318 pages Book Rating :4.4/5 (899 download)
Book Synopsis VLSI for Neural Networks and Artificial Intelligence by : Jose G. Delgado-Frias
Download or read book VLSI for Neural Networks and Artificial Intelligence written by Jose G. Delgado-Frias and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural network and artificial intelligence algorithrns and computing have increased not only in complexity but also in the number of applications. This in turn has posed a tremendous need for a larger computational power that conventional scalar processors may not be able to deliver efficiently. These processors are oriented towards numeric and data manipulations. Due to the neurocomputing requirements (such as non-programming and learning) and the artificial intelligence requirements (such as symbolic manipulation and knowledge representation) a different set of constraints and demands are imposed on the computer architectures/organizations for these applications. Research and development of new computer architectures and VLSI circuits for neural networks and artificial intelligence have been increased in order to meet the new performance requirements. This book presents novel approaches and trends on VLSI implementations of machines for these applications. Papers have been drawn from a number of research communities; the subjects span analog and digital VLSI design, computer design, computer architectures, neurocomputing and artificial intelligence techniques. This book has been organized into four subject areas that cover the two major categories of this book; the areas are: analog circuits for neural networks, digital implementations of neural networks, neural networks on multiprocessor systems and applications, and VLSI machines for artificial intelligence. The topics that are covered in each area are briefly introduced below.
Book Synopsis VLSI Artificial Neural Networks Engineering by : Mohamed I. Elmasry
Download or read book VLSI Artificial Neural Networks Engineering written by Mohamed I. Elmasry and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Hardware Annealing in Analog VLSI Neurocomputing by : Bank W. Lee
Download or read book Hardware Annealing in Analog VLSI Neurocomputing written by Bank W. Lee and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid advances in neural sciences and VLSI design technologies have provided an excellent means to boost the computational capability and efficiency of data and signal processing tasks by several orders of magnitude. With massively parallel processing capabilities, artificial neural networks can be used to solve many engineering and scientific problems. Due to the optimized data communication structure for artificial intelligence applications, a neurocomputer is considered as the most promising sixth-generation computing machine. Typical applica tions of artificial neural networks include associative memory, pattern classification, early vision processing, speech recognition, image data compression, and intelligent robot control. VLSI neural circuits play an important role in exploring and exploiting the rich properties of artificial neural networks by using pro grammable synapses and gain-adjustable neurons. Basic building blocks of the analog VLSI neural networks consist of operational amplifiers as electronic neurons and synthesized resistors as electronic synapses. The synapse weight information can be stored in the dynamically refreshed capacitors for medium-term storage or in the floating-gate of an EEPROM cell for long-term storage. The feedback path in the amplifier can continuously change the output neuron operation from the unity-gain configuration to a high-gain configuration. The adjustability of the vol tage gain in the output neurons allows the implementation of hardware annealing in analog VLSI neural chips to find optimal solutions very efficiently. Both supervised learning and unsupervised learning can be implemented by using the programmable neural chips.
Author :Jose G. Delgado-Frias Publisher :Springer Science & Business Media ISBN 13 :1461537525 Total Pages :411 pages Book Rating :4.4/5 (615 download)
Book Synopsis VLSI for Artificial Intelligence and Neural Networks by : Jose G. Delgado-Frias
Download or read book VLSI for Artificial Intelligence and Neural Networks written by Jose G. Delgado-Frias and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Cellular Neural Networks and Analog VLSI by : Leon Chua
Download or read book Cellular Neural Networks and Analog VLSI written by Leon Chua and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cellular Neural Networks and Analog VLSI brings together in one place important contributions and up-to-date research results in this fast moving area. Cellular Neural Networks and Analog VLSI serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
Book Synopsis Analog VLSI Integration of Massive Parallel Signal Processing Systems by : Peter Kinget
Download or read book Analog VLSI Integration of Massive Parallel Signal Processing Systems written by Peter Kinget and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: When comparing conventional computing architectures to the architectures of biological neural systems, we find several striking differences. Conventional computers use a low number of high performance computing elements that are programmed with algorithms to perform tasks in a time sequenced way; they are very successful in administrative applications, in scientific simulations, and in certain signal processing applications. However, the biological systems still significantly outperform conventional computers in perception tasks, sensory data processing and motory control. Biological systems use a completely dif ferent computing paradigm: a massive network of simple processors that are (adaptively) interconnected and operate in parallel. Exactly this massively parallel processing seems the key aspect to their success. On the other hand the development of VLSI technologies provide us with technological means to implement very complicated systems on a silicon die. Especially analog VLSI circuits in standard digital technologies open the way for the implement at ion of massively parallel analog signal processing systems for sensory signal processing applications and for perception tasks. In chapter 1 the motivations behind the emergence of the analog VLSI of massively parallel systems is discussed in detail together with the capabilities and !imitations of VLSI technologies and the required research and developments. Analog parallel signal processing drives for the development of very com pact, high speed and low power circuits. An important technologicallimitation in the reduction of the size of circuits and the improvement of the speed and power consumption performance is the device inaccuracies or device mismatch.
Book Synopsis Analog VLSI Circuits for the Perception of Visual Motion by : Alan A. Stocker
Download or read book Analog VLSI Circuits for the Perception of Visual Motion written by Alan A. Stocker and published by John Wiley & Sons. This book was released on 2006-03-30 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Analogue Neural VLSI by : Alan F. Murray
Download or read book Analogue Neural VLSI written by Alan F. Murray and published by . This book was released on 1994 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Neural Information Processing and VLSI by : Bing J. Sheu
Download or read book Neural Information Processing and VLSI written by Bing J. Sheu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis VLSI — Compatible Implementations for Artificial Neural Networks by : Sied Mehdi Fakhraie
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.
Book Synopsis VLSI Design of Neural Networks by : Ulrich Ramacher
Download or read book VLSI Design of Neural Networks written by Ulrich Ramacher and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: The early era of neural network hardware design (starting at 1985) was mainly technology driven. Designers used almost exclusively analog signal processing concepts for the recall mode. Learning was deemed not to cause a problem because the number of implementable synapses was still so low that the determination of weights and thresholds could be left to conventional computers. Instead, designers tried to directly map neural parallelity into hardware. The architectural concepts were accordingly simple and produced the so called interconnection problem which, in turn, made many engineers believe it could be solved by optical implementation in adequate fashion only. Furthermore, the inherent fault-tolerance and limited computation accuracy of neural networks were claimed to justify that little effort is to be spend on careful design, but most effort be put on technology issues. As a result, it was almost impossible to predict whether an electronic neural network would function in the way it was simulated to do. This limited the use of the first neuro-chips for further experimentation, not to mention that real-world applications called for much more synapses than could be implemented on a single chip at that time. Meanwhile matters have matured. It is recognized that isolated definition of the effort of analog multiplication, for instance, would be just as inappropriate on the part ofthe chip designer as determination of the weights by simulation, without allowing for the computing accuracy that can be achieved, on the part of the user.
Book Synopsis Neuromorphic Systems: Engineering Silicon From Neurobiology by : Alister Hamilton
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 276 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.
Book Synopsis Hardware Annealing in Analog VLSI Neurocomputing by : Bank W. Lee
Download or read book Hardware Annealing in Analog VLSI Neurocomputing written by Bank W. Lee and published by Springer. This book was released on 1990-12-31 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid advances in neural sciences and VLSI design technologies have provided an excellent means to boost the computational capability and efficiency of data and signal processing tasks by several orders of magnitude. With massively parallel processing capabilities, artificial neural networks can be used to solve many engineering and scientific problems. Due to the optimized data communication structure for artificial intelligence applications, a neurocomputer is considered as the most promising sixth-generation computing machine. Typical applica tions of artificial neural networks include associative memory, pattern classification, early vision processing, speech recognition, image data compression, and intelligent robot control. VLSI neural circuits play an important role in exploring and exploiting the rich properties of artificial neural networks by using pro grammable synapses and gain-adjustable neurons. Basic building blocks of the analog VLSI neural networks consist of operational amplifiers as electronic neurons and synthesized resistors as electronic synapses. The synapse weight information can be stored in the dynamically refreshed capacitors for medium-term storage or in the floating-gate of an EEPROM cell for long-term storage. The feedback path in the amplifier can continuously change the output neuron operation from the unity-gain configuration to a high-gain configuration. The adjustability of the vol tage gain in the output neurons allows the implementation of hardware annealing in analog VLSI neural chips to find optimal solutions very efficiently. Both supervised learning and unsupervised learning can be implemented by using the programmable neural chips.
