Neural Networks and Analog Computation

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Publisher : Springer Science & Business Media
ISBN 13 : 146120707X
Total Pages : 193 pages
Book Rating : 4.78/5 ( download)

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Book Synopsis Neural Networks and Analog Computation by : Hava T. Siegelmann

Download or read book Neural Networks and Analog Computation written by Hava T. Siegelmann and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Analog Computing

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110787741
Total Pages : 460 pages
Book Rating : 4.40/5 ( download)

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Book Synopsis Analog Computing by : Bernd Ulmann

Download or read book Analog Computing written by Bernd Ulmann and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-11-07 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Analog VLSI and Neural Systems

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Author :
Publisher : Addison Wesley Publishing Company
ISBN 13 :
Total Pages : 416 pages
Book Rating : 4.21/5 ( download)

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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

VLSI Design of Neural Networks

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Publisher : Springer Science & Business Media
ISBN 13 : 1461539943
Total Pages : 346 pages
Book Rating : 4.40/5 ( download)

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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.

The Spike

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Publisher : Princeton University Press
ISBN 13 : 0691213518
Total Pages : 232 pages
Book Rating : 4.14/5 ( download)

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Book Synopsis The Spike by : Mark Humphries

Download or read book The Spike written by Mark Humphries and published by Princeton University Press. This book was released on 2021-03-09 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: The story of a neural impulse and what it reveals about how our brains work We see the last cookie in the box and think, can I take that? We reach a hand out. In the 2.1 seconds that this impulse travels through our brain, billions of neurons communicate with one another, sending blips of voltage through our sensory and motor regions. Neuroscientists call these blips “spikes.” Spikes enable us to do everything: talk, eat, run, see, plan, and decide. In The Spike, Mark Humphries takes readers on the epic journey of a spike through a single, brief reaction. In vivid language, Humphries tells the story of what happens in our brain, what we know about spikes, and what we still have left to understand about them. Drawing on decades of research in neuroscience, Humphries explores how spikes are born, how they are transmitted, and how they lead us to action. He dives into previously unanswered mysteries: Why are most neurons silent? What causes neurons to fire spikes spontaneously, without input from other neurons or the outside world? Why do most spikes fail to reach any destination? Humphries presents a new vision of the brain, one where fundamental computations are carried out by spontaneous spikes that predict what will happen in the world, helping us to perceive, decide, and react quickly enough for our survival. Traversing neuroscience’s expansive terrain, The Spike follows a single electrical response to illuminate how our extraordinary brains work.

Neural Networks: Computational Models and Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 3540692258
Total Pages : 310 pages
Book Rating : 4.56/5 ( download)

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Book Synopsis Neural Networks: Computational Models and Applications by : Huajin Tang

Download or read book Neural Networks: Computational Models and Applications written by Huajin Tang and published by Springer Science & Business Media. This book was released on 2007-03-12 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks: Computational Models and Applications presents important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. The book offers a compact, insightful understanding of the broad and rapidly growing neural networks domain.

Neural Networks

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Publisher : World Scientific
ISBN 13 : 9789971509385
Total Pages : 200 pages
Book Rating : 4.85/5 ( download)

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Book Synopsis Neural Networks by : S?ren Brunak

Download or read book Neural Networks written by S?ren Brunak and published by World Scientific. This book was released on 1990 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both specialists and laymen will enjoy reading this book. Using a lively, non-technical style and images from everyday life, the authors present the basic principles behind computing and computers. The focus is on those aspects of computation that concern networks of numerous small computational units, whether biological neural networks or artificial electronic devices.

Analog VLSI Neural Networks

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Publisher : Springer Science & Business Media
ISBN 13 : 1461535824
Total Pages : 132 pages
Book Rating : 4.29/5 ( download)

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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 132 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.

Encyclopedia of Complexity and Systems Science

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Publisher : Springer
ISBN 13 : 9780387758886
Total Pages : 10398 pages
Book Rating : 4.87/5 ( download)

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Book Synopsis Encyclopedia of Complexity and Systems Science by :

Download or read book Encyclopedia of Complexity and Systems Science written by and published by Springer. This book was released on 2009-06-26 with total page 10398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This encyclopedia provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. It links fundamental concepts of mathematics and computational sciences to applications in the physical sciences, engineering, biomedicine, economics and the social sciences.

Non-Linear Feedback Neural Networks

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Publisher : Springer
ISBN 13 : 813221563X
Total Pages : 217 pages
Book Rating : 4.39/5 ( download)

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Book Synopsis Non-Linear Feedback Neural Networks by : Mohd. Samar Ansari

Download or read book Non-Linear Feedback Neural Networks written by Mohd. Samar Ansari and published by Springer. This book was released on 2013-09-03 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation.