Optical Computing And Neural Networks
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Optical Computing And Neural Networks
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Author : Hua-Kuang Liu
language : en
Publisher:
Release Date : 1992
Optical Computing And Neural Networks written by Hua-Kuang Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Computers categories.
Optical Neural Networks
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Author : Cornelia Denz
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Optical Neural Networks written by Cornelia Denz 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 2013-11-11 with Computers categories.
In recent years, there has been a rapid expansion in the field of nonlinear optics as weIl as in the field of neural computing. Up to date, no one would doubt that nonlinear optics is one of the most promising fields of realizing large neural network models due to their inherent parallelism, the use of the speed of light and their ability to process two-dimensional data arrays without carriers or transformation bottlenecks. This is the reason why so many of the interesting applications of nonlinear optics - associative memories, Hopfield networks and self-organized nets - are realized in an all optical way using nonlinear optical processing elements. Both areas attracting people from a wide variety of disciplines and judged by the proliferation of published papers, conferences, international collaborations and enterprises, more people than ever before are now in volved in research and applications in these two fields. These people all bring a different background to the area, and one of the aims of this book is to provide a common ground from which new development can grow. Another aim is to explain the basic concepts of neural computation as weIl as its nonlinear optical realizations to an interested audi ence. Therefore, the book is about the whole field of optical neural network applications, covering all the major approaches and their important results. Especially, it its an in troduction that develops the concepts and ideas from their simple basics through their formulation into powerful experimental neural net systems.
Optical Signal Processing Computing And Neural Networks
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Author : Frances T. S. Yu
language : en
Publisher: Wiley-Interscience
Release Date : 1992-11-19
Optical Signal Processing Computing And Neural Networks written by Frances T. S. Yu and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-11-19 with Computers categories.
In recent years, optical computing and optical neural networks research has enriched the field originally known as optical signal processing. Optical Signal Processing, Computing, and Neural Networks is a self-contained textbook that offers an introductory survey which examines photonics, linear and nonlinear signal processing, and numerical, symbolic, and neural computing. This comprehensive sourcebook is a basic text for students who lack an intensive background in optic, electromagnetic, computer, and neural network theories. It will also serve as a working reference for optical physicists and engineers involved in current research and development of modern optical signal processing that includes optical computing and neural networks. The first chapter of this book contains the basic coherent theory and concepts of optical transformation. The second chapter introduces the fundamental concept of optical signal processing and its architectures. The third chapter presents selected applications in coherent optics while the fourth chapter discusses white-light processing and its applications. The advances of spatial-light modulators are discussed as well as hybrid-optical architectures using spatial-light modulators in later chapters. Applications of photorefractive crystals in optical signal processing are presented in chapter 7. Digital-optical computing is described in chapter 8 while optical neural networks and their architectures, designs, and models are thoroughly covered in chapter 9. Examples and experimental results are included throughout the book to emphasize the concepts. Chapters include problem sets, 330 throughout, that reinforce key elements in the text.
Optical Computer Architectures
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Author : Alastair D. McAulay
language : en
Publisher: Wiley-Interscience
Release Date : 1991-01-16
Optical Computer Architectures written by Alastair D. McAulay and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-01-16 with Computers categories.
Optics is entering all phases of computer technology. By providing new research and ideas, it brings the reader up to date on how and why optics is likely to be used in next generation computers and at the same time explains the unique advantage optics enjoys over conventional electronics and why this trend will continue. Covered are basic optical concepts such as mathematical derivations, optical devices for optical computing, optical associative memories, optical interconnections, and optical logic. Also suggested are a number of research activities that are reinforcing the trend toward optics in computing, including neural networks, the software crisis, highly parallel computation, progress in new semiconductors, the decreasing cost of laser diodes, communication industry investments in fiber optics, and advances in optical devices. Exercises, solutions sets, and examples are provided.
An Introduction To Optics In Computers
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Author : Henri H. Arsenault
language : en
Publisher: SPIE Press
Release Date : 1992
An Introduction To Optics In Computers written by Henri H. Arsenault and has been published by SPIE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Computers categories.
This volume surveys the entire field of optical computing. The emphasis is on breadth of coverage. The book is descriptive, the authors minimize the use of mathematics, and it is therefore most suitable for those who require an overall view of what is going on in this field. A detailed comparison is given of the capabilities of electronics and optics, and the degree to which these capabilities have been achieved is indicated. Other areas of focus include optical computing architectures, components and technologies, optical interconnects, and optical neural nets. Approximately 300 references to key works in the field are included.
Massively Parallel Optical And Neural Computing In The United States
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Author : Gilbert Kalb
language : en
Publisher: IOS Press
Release Date : 1992
Massively Parallel Optical And Neural Computing In The United States written by Gilbert Kalb and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Computers categories.
A survey of products and research projects in the field of highly parallel, optical and neural computers in the USA. It covers operating systems, language projects and market analysis, as well as optical computing devices and optical connections of electronic parts.
Neural Networks And Analog Computation
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Author : Hava Siegelmann
language : en
Publisher: Springer Science & Business Media
Release Date : 1998-12-01
Neural Networks And Analog Computation written by Hava Siegelmann 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 1998-12-01 with Computers categories.
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.
Optical Computing Future
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Author : Sterling Blackwood
language : en
Publisher: Publifye AS
Release Date : 2025-03-04
Optical Computing Future written by Sterling Blackwood and has been published by Publifye AS this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-04 with Technology & Engineering categories.
Optical Computing Future explores the exciting possibility of using light, or photonics, instead of electrons to revolutionize computation. It suggests that optical computing could overcome the limits of traditional electronic systems, achieving unprecedented speeds and energy efficiency. The book highlights how the speed of light and potential for parallel processing offer significant advantages, especially as Moore's Law slows and energy demands increase. Optical transistors and switches are key components discussed, revealing the challenges and innovations in making these tiny light-based devices a reality. The book begins with the basics of optics and photonics, contrasting them with electronic computing principles. It then delves into the development of essential optical components and architectures, examining their strengths and weaknesses. Covering materials science, electrical engineering, and computer science, the book emphasizes the need for collaboration across disciplines. For example, developing new optical materials is crucial for advancing optical computing capabilities. Concluding with practical applications, the book illustrates how optical computing can be used in high-performance computing, artificial intelligence, and data centers. It provides a balanced view of the advantages and disadvantages compared to electronic computing, allowing readers to form their own opinions on this rapidly evolving field.
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.
Artificial Neural Networks
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Author : Kevin L. Priddy
language : en
Publisher: SPIE Press
Release Date : 2005
Artificial Neural Networks written by Kevin L. Priddy and has been published by SPIE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.
This tutorial text provides the reader with an understanding of artificial neural networks (ANNs), and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed, and the data collection processes, to the many ways ANNs are being used today. The material is presented with a minimum of math (although the mathematical details are included in the appendices for interested readers), and with a maximum of hands-on experience. All specialized terms are included in a glossary. The result is a highly readable text that will teach the engineer the guiding principles necessary to use and apply artificial neural networks.