Neural Networks and Analog Computation

1998-12-01

The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines.

Author: Hava Siegelmann

Publisher: Springer Science & Business Media

ISBN: 0817639497

Category: Computers

Page: 208

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The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnected in an intricate structure. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models. On a mathematical level, the treatment of neural computations enriches the theory of computation but also explicated the computational complexity associated with biological networks, adaptive engineering tools, and related models from the fields of control theory and nonlinear dynamics. The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines. In addition, the work may provide the base of a graduate-level seminar in neural networks for computer science students.
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Neural Networks and Analog Computation

2012-12-06

In the previous chapter we introduced the not yet fully sculpted general framework of analog computation, and contrasted it with digital computation. The neural network model, which fits in this framework, was proven throughout this ...

Author: Hava T. Siegelmann

Publisher: Springer Science & Business Media

ISBN: 9781461207078

Category: Computers

Page: 181

View: 596

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The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnected in an intricate structure. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models. On a mathematical level, the treatment of neural computations enriches the theory of computation but also explicated the computational complexity associated with biological networks, adaptive engineering tools, and related models from the fields of control theory and nonlinear dynamics. The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines. In addition, the work may provide the base of a graduate-level seminar in neural networks for computer science students.
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Neural Networks and Analog Computation

2012-10-21

The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines.

Author: Hava Siegelmann

Publisher: Birkhäuser

ISBN: 1461268753

Category: Computers

Page: 181

View: 766

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The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnected in an intricate structure. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models. On a mathematical level, the treatment of neural computations enriches the theory of computation but also explicated the computational complexity associated with biological networks, adaptive engineering tools, and related models from the fields of control theory and nonlinear dynamics. The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines. In addition, the work may provide the base of a graduate-level seminar in neural networks for computer science students.
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Artificial Neural Networks and Machine Learning ICANN 2019 Theoretical Neural Computation

2019-09-09

Balcázar, J.L., Gavald`a, R., Siegelmann, H.T.: Computational power of neural networks: A characterization in ... Neural Netw. 61, 85–117 (2015) 10. Siegelmann, H.T.: Neural Networks and Analog Computation: Beyond the Turing Limit.

Author: Igor V. Tetko

Publisher: Springer Nature

ISBN: 9783030304874

Category: Computers

Page: 839

View: 272

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The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.
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Analog Computing

2022-11-07

The book “Analog Computing” has established itself over the past decade as the standard textbook on the subject and has been substantially extended in this second edition, which includes more than 300 additional bibliographical entries, ...

Author: Bernd Ulmann

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 9783110787740

Category: Computers

Page: 460

View: 256

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Analog computing is one of the main pillars of Unconventional Computing. Almost forgotten for decades, we now see an ever-increasing interest in electronic analog computing because it offers a path to high-performance and highly energy-efficient computing. These characteristics are of great importance in a world where vast amounts of electric energy are consumed by today’s computer systems. Analog computing can deliver efficient solutions to many computing problems, ranging from general purpose analog computation to specialised systems like analog artificial neural networks. The book “Analog Computing” has established itself over the past decade as the standard textbook on the subject and has been substantially extended in this second edition, which includes more than 300 additional bibliographical entries, and has been expanded in many areas to include much greater detail. These enhancements will confirm this book’s status as the leading work in the field. It covers the history of analog computing from the Antikythera Mechanism to recent electronic analog computers and uses a wide variety of worked examples to provide a comprehensive introduction to programming analog computers. It also describes hybrid computers, digital differential analysers, the simulation of analog computers, stochastic computers, and provides a comprehensive treatment of classic and current analog computer applications. The last chapter looks into the promising future of analog computing.
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The Handbook of Brain Theory and Neural Networks

2003

lntroduction The computational overhead required to simulate artilicial neural network iANNi models. whether simplistic or ... One commonly held belief in the ANN research community is that analog computation. in which signals are ...

Author: Michael A. Arbib

Publisher: MIT Press

ISBN: 9780262011976

Category: Computers

Page: 1328

View: 225

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This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).
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Artificial Higher Order Neural Networks for Computer Science and Engineering Trends for Emerging Applications

2010-02-28

... in Neural Networks. Journal of the Brazilian Computer Society, 8(3), 58–70. doi:10.1590/S0104-65002003000100005 Osório, F., & Amy, B. (1999). ... Neural Networks and Analog Computation: Beyond the Turing Limit, Birkhäuser.

Author: Zhang, Ming

Publisher: IGI Global

ISBN: 9781615207121

Category: Computers

Page: 660

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"This book introduces and explains Higher Order Neural Networks (HONNs) to people working in the fields of computer science and computer engineering, and how to use HONNS in these areas"--Provided by publisher.
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Limitations and Future Trends in Neural Computation

2003

[ 55 ] I. Parberry , A primer on the complexity theory of neural networks , in : R.B. Banerji , ed . , Formal Techniques in ... [ 61 ] H.T. Siegelmann , Neural Networks and Analog Computation : Beyond the Turing Limit , Birkhäuser ...

Author: Sergey Ablameyko

Publisher: IOS Press

ISBN: 1586033247

Category: Electronic books

Page: 262

View: 854

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This work reports critical analyses on complexity issues in the continuum setting and on generalization to new examples, which are two basic milestones in learning from examples in connectionist models. It also covers up-to-date developments in computational mathematics.
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Analog VLSI Neural Networks

2012-12-06

Teuvo Kohonen, “An introduction to neural computing,” Neural Networks, Vol. 1, No. 1, pp. 3–16, 1988. Bart Kosko, Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence, Prentice Hall: Englewood Cliffs, ...

Author: Yoshiyasu Takefuji

Publisher: Springer Science & Business Media

ISBN: 9781461535829

Category: Technology & Engineering

Page: 131

View: 823

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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.
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Theory and Practice of Natural Computing

2018-12-05

extra analog units. Nevertheless, the ultimate goal is to prove a proper “natural” hierarchy of neural networks between integer and rational weights similarly as it is known between rational and real weights [2] and possibly, ...

Author: David Fagan

Publisher: Springer

ISBN: 9783030040703

Category: Computers

Page: 474

View: 637

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This book constitutes the refereed proceedings of the 7th International Conference on Theory and Practice of Natural Computing, TPNC 2017, held in Dublin, Ireland, in December 2018. The 35 full papers presented in this book, together with one invited talk, were carefully reviewed and selected from 69 submissions. The papers are organized around the following topical sections: applications of natural computing as algorithms, bioinformatics, control, cryptography, design, economics. The more theoretical contributions handle with artificial chemistry, artificial immune systems, artificial life, cellular automata, cognitive computing, cognitive engineering, cognitive robotics, collective behaviour, complex systems, computational intelligence, computational social science, computing with words, developmental systems, DNA computing, DNA nanotechnology, evolutionary algorithms, evolutionary computing, evolutionary game theory, fractal geometry, fuzzy control, fuzzy logic, fuzzy sets, fuzzy systems, genetic algorithms, genetic programming, granular computing, heuristics, intelligent agents, intelligent systems, machine intelligence, molecular programming, neural computing, neural networks, quantum communication, quantum computing, rough sets, self-assembly.
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