Neural Information Processing And Vlsi
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Neural Information Processing And Vlsi
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Author : Bing J. Sheu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Neural Information Processing And Vlsi written by Bing J. Sheu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
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 beenespecially 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.
Advances In Neural Information Processing Systems 19
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Author : Bernhard Schölkopf
language : en
Publisher: MIT Press
Release Date : 2007
Advances In Neural Information Processing Systems 19 written by Bernhard Schölkopf and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Artificial intelligence categories.
The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation and machine learning. This volume contains the papers presented at the December 2006 meeting, held in Vancouver.
Vlsi Design Of Neural Networks
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Author : Ulrich Ramacher
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Vlsi Design Of Neural Networks written by Ulrich Ramacher and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
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.
Neural Information Processing
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Author : Minho Lee
language : en
Publisher: Springer
Release Date : 2013-10-29
Neural Information Processing written by Minho Lee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-29 with Computers categories.
The three volume set LNCS 8226, LNCS 8227, and LNCS 8228 constitutes the proceedings of the 20th International Conference on Neural Information Processing, ICONIP 2013, held in Daegu, Korea, in November 2013. The 180 full and 75 poster papers presented together with 4 extended abstracts were carefully reviewed and selected from numerous submissions. These papers cover all major topics of theoretical research, empirical study and applications of neural information processing research. The specific topics covered are as follows: cognitive science and artificial intelligence; learning theory, algorithms and architectures; computational neuroscience and brain imaging; vision, speech and signal processing; control, robotics and hardware technologies and novel approaches and applications.
Advances In Neural Information Processing Systems 15
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Author : Suzanna Becker
language : en
Publisher: MIT Press
Release Date : 2003
Advances In Neural Information Processing Systems 15 written by Suzanna Becker and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.
Proceedings of the 2002 Neural Information Processing Systems Conference.
Neural Information Processing
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Author : Long Cheng
language : en
Publisher: Springer
Release Date : 2018-12-03
Neural Information Processing written by Long Cheng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-03 with Computers categories.
The seven-volume set of LNCS 11301-11307, constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The second volume, LNCS 11302, is organized in topical sections on other neural network models, stability analysis, optimization, and supervised learning.
Advances In Neural Information Processing Systems 10
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Author : Michael I. Jordan
language : en
Publisher: MIT Press
Release Date : 1998
Advances In Neural Information Processing Systems 10 written by Michael I. Jordan and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computers categories.
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.
Analog Vlsi Integration Of Massive Parallel Signal Processing Systems
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Author : Peter Kinget
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Analog Vlsi Integration Of Massive Parallel Signal Processing Systems written by Peter Kinget and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Technology & Engineering categories.
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.
Vlsi For Artificial Intelligence And Neural Networks
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Author : Jose G. Delgado-Frias
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Vlsi For Artificial Intelligence And Neural Networks written by Jose G. Delgado-Frias and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
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.
Advances In Neural Information Processing Systems 7
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Author : Gerald Tesauro
language : en
Publisher: MIT Press
Release Date : 1995
Advances In Neural Information Processing Systems 7 written by Gerald Tesauro and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
November 28-December 1, 1994, Denver, Colorado NIPS is the longest running annual meeting devoted to Neural Information Processing Systems. Drawing on such disparate domains as neuroscience, cognitive science, computer science, statistics, mathematics, engineering, and theoretical physics, the papers collected in the proceedings of NIPS7 reflect the enduring scientific and practical merit of a broad-based, inclusive approach to neural information processing. The primary focus remains the study of a wide variety of learning algorithms and architectures, for both supervised and unsupervised learning. The 139 contributions are divided into eight parts: Cognitive Science, Neuroscience, Learning Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Visual Processing, and Applications. Topics of special interest include the analysis of recurrent nets, connections to HMMs and the EM procedure, and reinforcement- learning algorithms and the relation to dynamic programming. On the theoretical front, progress is reported in the theory of generalization, regularization, combining multiple models, and active learning. Neuroscientific studies range from the large-scale systems such as visual cortex to single-cell electrotonic structure, and work in cognitive scientific is closely tied to underlying neural constraints. There are also many novel applications such as tokamak plasma control, Glove-Talk, and hand tracking, and a variety of hardware implementations, with particular focus on analog VLSI.