Search results for: neural-network-analog-vlsi-multipliers

Technology 2001

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Analog VLSI Neural Networks

Author : Yoshiyasu Takefuji
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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.

Science Abstracts

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Cellular Neural Networks and Analog VLSI

Author : Leon Chua
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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.

Artificial Neural Networks 2

Author : Igor Aleksander
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This two-volume proceedings compilation is a selection of research papers presented at the ICANN-92. The scope of the volumes is interdisciplinary, ranging from the minutiae of VLSI hardware, to new discoveries in neurobiology, through to the workings of the human mind. USA and European research is well represented, including not only new thoughts from old masters but also a large number of first-time authors who are ensuring the continued development of the field.

Analog VHDL

Author : Andrzej T. Rosinski
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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 Integration of Massive Parallel Signal Processing Systems

Author : Peter Kinget
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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.

Adaptive Analog VLSI Neural Systems

Author : M. Jabri
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This book approaches VLSI neural networks from a practical viewpoint, using case studies to show the full process of VLSI implementation of a network, and addressing the important issues of learning algorithms and limited precision effects. System aspects and low-power implementation issues are also covered. The authors are all international figures in the field from AT&T Bell Labs, Bellcore and SEDAL.

IEEE International Conference on Electronics Circuits and Systems

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VLSI for Artificial Intelligence and Neural Networks

Author : Jose G. Delgado-Frias
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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.

Technology 2001 The Second National Technology Transfer Conference and Exposition Volume 1

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NASA Conference Publication

Author : United States. National Aeronautics and Space Administration
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Index to IEEE Publications

Author : Institute of Electrical and Electronics Engineers
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Applications of Artificial Neural Networks

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VLSI for Neural Networks and Artificial Intelligence

Author : Jose G. Delgado-Frias
File Size : 40.80 MB
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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.

1995 Second New Zealand International Two Stream Conference on Artificial Neural Networks and Expert Systems November 20 23 1995 Dunedin New Zealand

Author : New Zealand Computer Society
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Annotation Takes account of the new concept in artificial intelligence called soft computing, in which the similarities among the various methods for building intelligent information systems make them alternative choices for a particular application, yet their differences also make them potential complements to be used together in a single system. The 19 invited and 77 session papers cover neural networks, fuzzy logic systems, genetic algorithms and evolutionary programming, expert systems, machine learning, hybrid systems, and applications. No subject index. Annotation copyright by Book News, Inc., Portland, OR.

Information Optics

Author : American Institute of Physics
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This fifth edition of the Workshop on Information Optics (WIO) was mainly focused on the latest advances in optics and information theory and applications. This volume contains peer-reviewed papers that cover 3D imaging, image processing, signal processing, time-frequency representations, super resolution, optical sensors, and wireless sensors.

1993 IEEE International Conference on Neural Networks San Francisco California March 28 April 1 1993

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VLSI Design 95

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Presents papers from the January 1995 conference. Topics include routing, hardware-software design/CAD, sequential automatic test pattern generation, logic synthesis, VLSI arithmetic, and chip design. Includes tools and technology poster sessions, and a panel discussion on India's role in the VLSI w

IEEE International Conference on Neural Networks

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