Photonic Reservoir Computing PDF Download
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Author: Daniel Brunner
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110583496
Category : Science
Languages : en
Pages : 276
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Book Description
Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.
Author: Daniel Brunner
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110583496
Category : Science
Languages : en
Pages : 276
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Book Description
Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.
Author: Cornelia Denz
Publisher: Springer Science & Business Media
ISBN: 3663122727
Category : Computers
Languages : en
Pages : 467
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Book Description
During the next years neural networks and systems amenable to instructions will extend their influence in science and technology. A prominent point of interest in this field is assigned to optical networks: they are small and flexible, and due to their ability of parallel processing they are devoted to the construction of small systems. This monograph explains the fundamentals of optical neural networks to physicists, engineers and device constructors.
Author: Kevin L. Priddy
Publisher: SPIE Press
ISBN: 9780819459879
Category : Computers
Languages : en
Pages : 184
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Book Description
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.
Author: Paul R. Prucnal
Publisher: CRC Press
ISBN: 1498725244
Category : Science
Languages : en
Pages : 412
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Book Description
This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.
Author: Michael J. Connelly
Publisher: Springer Science & Business Media
ISBN: 0306481561
Category : Technology & Engineering
Languages : en
Pages : 172
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Book Description
The semiconductor optical amplifier has emerged as an important component in many optical fibre communication, switching and signal processing systems. This invaluable information source provides a comprehensive and detailed treatment of the design and applications of SOAs.
Author: Pochi Yeh
Publisher: World Scientific
ISBN: 9789810214432
Category : Science
Languages : en
Pages : 628
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Book Description
This book, intended for students, researchers and engineers, is a collection of classic papers on photorefractive nonlinear optics. Included are landmark papers on fundamental photorefractive phenomena, two-wave mixing, four-wave mixing, phase conjugators and resonators, material growth and physics, and applications in image processing, optical storage and optical computing.
Author: Francis T. S. Yu
Publisher: Cambridge University Press
ISBN: 9780521465175
Category : Computers
Languages : en
Pages : 460
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Book Description
A comprehensive review of optical pattern recognition techniques and implementations, for graduate students and researchers.
Author:
Publisher:
ISBN: 9780127412528
Category :
Languages : en
Pages :
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Book Description
Author: Alastair D. McAulay
Publisher: Wiley-Interscience
ISBN:
Category : Computers
Languages : en
Pages : 568
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Book Description
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.
Author: Katy Warr
Publisher: "O'Reilly Media, Inc."
ISBN: 1492044903
Category : Computers
Languages : en
Pages : 233
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Book Description
As deep neural networks (DNNs) become increasingly common in real-world applications, the potential to deliberately "fool" them with data that wouldn’t trick a human presents a new attack vector. This practical book examines real-world scenarios where DNNs—the algorithms intrinsic to much of AI—are used daily to process image, audio, and video data. Author Katy Warr considers attack motivations, the risks posed by this adversarial input, and methods for increasing AI robustness to these attacks. If you’re a data scientist developing DNN algorithms, a security architect interested in how to make AI systems more resilient to attack, or someone fascinated by the differences between artificial and biological perception, this book is for you. Delve into DNNs and discover how they could be tricked by adversarial input Investigate methods used to generate adversarial input capable of fooling DNNs Explore real-world scenarios and model the adversarial threat Evaluate neural network robustness; learn methods to increase resilience of AI systems to adversarial data Examine some ways in which AI might become better at mimicking human perception in years to come
