Reservoir Computing

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Reservoir Computing

Author : Kohei Nakajima
Publisher : Springer Nature
ISBN 13 : 9811316872
Total Pages : 463 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Reservoir Computing by : Kohei Nakajima

Download or read book Reservoir Computing written by Kohei Nakajima and published by Springer Nature. This book was released on 2021-08-05 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first comprehensive book about reservoir computing (RC). RC is a powerful and broadly applicable computational framework based on recurrent neural networks. Its advantages lie in small training data set requirements, fast training, inherent memory and high flexibility for various hardware implementations. It originated from computational neuroscience and machine learning but has, in recent years, spread dramatically, and has been introduced into a wide variety of fields, including complex systems science, physics, material science, biological science, quantum machine learning, optical communication systems, and robotics. Reviewing the current state of the art and providing a concise guide to the field, this book introduces readers to its basic concepts, theory, techniques, physical implementations and applications. The book is sub-structured into two major parts: theory and physical implementations. Both parts consist of a compilation of chapters, authored by leading experts in their respective fields. The first part is devoted to theoretical developments of RC, extending the framework from the conventional recurrent neural network context to a more general dynamical systems context. With this broadened perspective, RC is not restricted to the area of machine learning but is being connected to a much wider class of systems. The second part of the book focuses on the utilization of physical dynamical systems as reservoirs, a framework referred to as physical reservoir computing. A variety of physical systems and substrates have already been suggested and used for the implementation of reservoir computing. Among these physical systems which cover a wide range of spatial and temporal scales, are mechanical and optical systems, nanomaterials, spintronics, and quantum many body systems. This book offers a valuable resource for researchers (Ph.D. students and experts alike) and practitioners working in the field of machine learning, artificial intelligence, robotics, neuromorphic computing, complex systems, and physics.

Photonic Reservoir Computing

Author : Daniel Brunner
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110582112
Total Pages : 391 pages
Book Rating : 4.1/5 (15 download)

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Book Synopsis Photonic Reservoir Computing by : Daniel Brunner

Download or read book Photonic Reservoir Computing written by Daniel Brunner and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-07-08 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Computational Matter

Author : Susan Stepney
Publisher : Springer
ISBN 13 : 3319658263
Total Pages : 337 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Computational Matter by : Susan Stepney

Download or read book Computational Matter written by Susan Stepney and published by Springer. This book was released on 2018-07-20 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is concerned with computing in materio: that is, unconventional computing performed by directly harnessing the physical properties of materials. It offers an overview of the field, covering four main areas of interest: theory, practice, applications and implications. Each chapter synthesizes current understanding by deliberately bringing together researchers across a collection of related research projects. The book is useful for graduate students, researchers in the field, and the general scientific reader who is interested in inherently interdisciplinary research at the intersections of computer science, biology, chemistry, physics, engineering and mathematics.

Photonic Reservoir Computing

Author : Daniel Brunner
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110583496
Total Pages : 277 pages
Book Rating : 4.1/5 (15 download)

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Book Synopsis Photonic Reservoir Computing by : Daniel Brunner

Download or read book Photonic Reservoir Computing written by Daniel Brunner and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-07-08 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Neural Networks - ICANN 2008

Author : Vera Kurkova-Pohlova
Publisher : Springer
ISBN 13 : 3540875360
Total Pages : 1026 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Artificial Neural Networks - ICANN 2008 by : Vera Kurkova-Pohlova

Download or read book Artificial Neural Networks - ICANN 2008 written by Vera Kurkova-Pohlova and published by Springer. This book was released on 2008-09-08 with total page 1026 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set LNCS 5163 and LNCS 5164 constitutes the refereed proceedings of the 18th International Conference on Artificial Neural Networks, ICANN 2008, held in Prague Czech Republic, in September 2008. The 200 revised full papers presented were carefully reviewed and selected from more than 300 submissions. The first volume contains papers on mathematical theory of neurocomputing, learning algorithms, kernel methods, statistical learning and ensemble techniques, support vector machines, reinforcement learning, evolutionary computing, hybrid systems, self-organization, control and robotics, signal and time series processing and image processing.

From Parallel to Emergent Computing

Author : Andrew Adamatzky
Publisher : CRC Press
ISBN 13 : 1351681923
Total Pages : 608 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis From Parallel to Emergent Computing by : Andrew Adamatzky

Download or read book From Parallel to Emergent Computing written by Andrew Adamatzky and published by CRC Press. This book was released on 2019-03-13 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern computing relies on future and emergent technologies which have been conceived via interaction between computer science, engineering, chemistry, physics and biology. This highly interdisciplinary book presents advances in the fields of parallel, distributed and emergent information processing and computation. The book represents major breakthroughs in parallel quantum protocols, elastic cloud servers, structural properties of interconnection networks, internet of things, morphogenetic collective systems, swarm intelligence and cellular automata, unconventionality in parallel computation, algorithmic information dynamics, localized DNA computation, graph-based cryptography, slime mold inspired nano-electronics and cytoskeleton computers. Features Truly interdisciplinary, spanning computer science, electronics, mathematics and biology Covers widely popular topics of future and emergent computing technologies, cloud computing, parallel computing, DNA computation, security and network analysis, cryptography, and theoretical computer science Provides unique chapters written by top experts in theoretical and applied computer science, information processing and engineering From Parallel to Emergent Computing provides a visionary statement on how computing will advance in the next 25 years and what new fields of science will be involved in computing engineering. This book is a valuable resource for computer scientists working today, and in years to come.

Advances in Unconventional Computing

Author : Andrew Adamatzky
Publisher : Springer
ISBN 13 : 3319339249
Total Pages : 874 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Advances in Unconventional Computing by : Andrew Adamatzky

Download or read book Advances in Unconventional Computing written by Andrew Adamatzky and published by Springer. This book was released on 2016-07-18 with total page 874 pages. Available in PDF, EPUB and Kindle. Book excerpt: The unconventional computing is a niche for interdisciplinary science, cross-bred of computer science, physics, mathematics, chemistry, electronic engineering, biology, material science and nanotechnology. The aims of this book are to uncover and exploit principles and mechanisms of information processing in and functional properties of physical, chemical and living systems to develop efficient algorithms, design optimal architectures and manufacture working prototypes of future and emergent computing devices. This first volume presents theoretical foundations of the future and emergent computing paradigms and architectures. The topics covered are computability, (non-)universality and complexity of computation; physics of computation, analog and quantum computing; reversible and asynchronous devices; cellular automata and other mathematical machines; P-systems and cellular computing; infinity and spatial computation; chemical and reservoir computing. The book is the encyclopedia, the first ever complete authoritative account, of the theoretical and experimental findings in the unconventional computing written by the world leaders in the field. All chapters are self-contains, no specialist background is required to appreciate ideas, findings, constructs and designs presented. This treatise in unconventional computing appeals to readers from all walks of life, from high-school pupils to university professors, from mathematicians, computers scientists and engineers to chemists and biologists.

DNA Computing and Molecular Programming

Author : David Soloveichik
Publisher : Springer
ISBN 13 : 3319019287
Total Pages : 210 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis DNA Computing and Molecular Programming by : David Soloveichik

Download or read book DNA Computing and Molecular Programming written by David Soloveichik and published by Springer. This book was released on 2013-09-19 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Conference on DNA Computing and Molecular Programming, DNA 19, held in Tempe, AZ, USA, in September 2013. The 14 full papers presented were carefully selected from 29 submissions. The papers are organized in many disciplines (including mathematics, computer science, physics, chemistry, material science and biology) to address the analysis, design, and synthesis of information-based molecular systems.

Artificial Neural Networks – ICANN 2009

Author : Cesare Alippi
Publisher : Springer Science & Business Media
ISBN 13 : 3642042732
Total Pages : 1062 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Artificial Neural Networks – ICANN 2009 by : Cesare Alippi

Download or read book Artificial Neural Networks – ICANN 2009 written by Cesare Alippi and published by Springer Science & Business Media. This book was released on 2009-09-03 with total page 1062 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is part of the two-volume proceedings of the 19th International Conf- ence on Artificial Neural Networks (ICANN 2009), which was held in Cyprus during September 14–17, 2009. The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS). ICANN 2009 was technically sponsored by the IEEE Computational Intel- gence Society. This series of conferences has been held annually since 1991 in various European countries and covers the field of neurocomputing, learning systems and related areas. Artificial neural networks provide an information-processing structure inspired by biological nervous systems. They consist of a large number of highly interconnected processing elements, with the capability of learning by example. The field of artificial neural networks has evolved significantly in the last two decades, with active partici- tion from diverse fields, such as engineering, computer science, mathematics, artificial intelligence, system theory, biology, operations research, and neuroscience. Artificial neural networks have been widely applied for pattern recognition, control, optimization, image processing, classification, signal processing, etc.

Application of FPGA to Real‐Time Machine Learning

Author : Piotr Antonik
Publisher : Springer
ISBN 13 : 3319910531
Total Pages : 171 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Application of FPGA to Real‐Time Machine Learning by : Piotr Antonik

Download or read book Application of FPGA to Real‐Time Machine Learning written by Piotr Antonik and published by Springer. This book was released on 2018-05-18 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book lies at the interface of machine learning – a subfield of computer science that develops algorithms for challenging tasks such as shape or image recognition, where traditional algorithms fail – and photonics – the physical science of light, which underlies many of the optical communications technologies used in our information society. It provides a thorough introduction to reservoir computing and field-programmable gate arrays (FPGAs). Recently, photonic implementations of reservoir computing (a machine learning algorithm based on artificial neural networks) have made a breakthrough in optical computing possible. In this book, the author pushes the performance of these systems significantly beyond what was achieved before. By interfacing a photonic reservoir computer with a high-speed electronic device (an FPGA), the author successfully interacts with the reservoir computer in real time, allowing him to considerably expand its capabilities and range of possible applications. Furthermore, the author draws on his expertise in machine learning and FPGA programming to make progress on a very different problem, namely the real-time image analysis of optical coherence tomography for atherosclerotic arteries.

Computational Vision and Bio-Inspired Computing

Author : S. Smys
Publisher : Springer Nature
ISBN 13 : 9811695733
Total Pages : 877 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Computational Vision and Bio-Inspired Computing by : S. Smys

Download or read book Computational Vision and Bio-Inspired Computing written by S. Smys and published by Springer Nature. This book was released on 2022-03-30 with total page 877 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers from the 5th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2021), held in Coimbatore, India, during November 25–26, 2021. This book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. It also contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.

Artificial General Intelligence

Author : Jürgen Schmidhuber
Publisher : Springer Science & Business Media
ISBN 13 : 3642228860
Total Pages : 427 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Artificial General Intelligence by : Jürgen Schmidhuber

Download or read book Artificial General Intelligence written by Jürgen Schmidhuber and published by Springer Science & Business Media. This book was released on 2011-07-19 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Conference on Artificial General Intelligence, AGI 2011, held in Mountain View, CA, USA, in August 2011. The 28 revised full papers and 26 short papers were carefully reviewed and selected from 103 submissions. The papers are written by leading academic and industry researchers involved in scientific and engineering work and focus on the creation of AI systems possessing general intelligence at the human level and beyond.

Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions

Author : Igor V. Tetko
Publisher : Springer Nature
ISBN 13 : 3030304930
Total Pages : 872 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions by : Igor V. Tetko

Download or read book Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions written by Igor V. Tetko and published by Springer Nature. This book was released on 2019-09-10 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Semiconductor Lasers

Author : Junji Ohtsubo
Publisher : Springer
ISBN 13 : 3319561383
Total Pages : 679 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Semiconductor Lasers by : Junji Ohtsubo

Download or read book Semiconductor Lasers written by Junji Ohtsubo and published by Springer. This book was released on 2017-05-03 with total page 679 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the fascinating recent advances made concerning the chaos, stability and instability of semiconductor lasers, and discusses their applications and future prospects in detail. It emphasizes the dynamics in semiconductor lasers by optical and electronic feedback, optical injection, and injection current modulation. Applications of semiconductor laser chaos, control and noise, and semiconductor lasers are also demonstrated. Semiconductor lasers with new structures, such as vertical-cavity surface-emitting lasers and broad-area semiconductor lasers, are intriguing and promising devices. Current topics include fast physical number generation using chaotic semiconductor lasers for secure communication, development of chaos, quantum-dot semiconductor lasers and quantum-cascade semiconductor lasers, and vertical-cavity surface-emitting lasers. This fourth edition has been significantly expanded to reflect the latest developments. The fundamental theory of laser chaos and the chaotic dynamics in semiconductor lasers are discussed, but also for example the method of self-mixing interferometry in quantum-cascade lasers, which is indispensable in practical applications. Further, this edition covers chaos synchronization between two lasers and the application to secure optical communications. Another new topic is the consistency and synchronization property of many coupled semiconductor lasers in connection with the analogy of the dynamics between synaptic neurons and chaotic semiconductor lasers, which are compatible nonlinear dynamic elements. In particular, zero-lag synchronization between distant neurons plays a crucial role for information processing in the brain. Lastly, the book presents an application of the consistency and synchronization property in chaotic semiconductor lasers, namely a type of neuro-inspired information processing referred to as reservoir computing.

VLSI and Hardware Implementations using Modern Machine Learning Methods

Author : Sandeep Saini
Publisher : CRC Press
ISBN 13 : 1000523845
Total Pages : 292 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis VLSI and Hardware Implementations using Modern Machine Learning Methods by : Sandeep Saini

Download or read book VLSI and Hardware Implementations using Modern Machine Learning Methods written by Sandeep Saini and published by CRC Press. This book was released on 2021-12-31 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Near-sensor and In-sensor Computing

Author : Yang Chai
Publisher : Springer Nature
ISBN 13 : 3031115066
Total Pages : 237 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Near-sensor and In-sensor Computing by : Yang Chai

Download or read book Near-sensor and In-sensor Computing written by Yang Chai and published by Springer Nature. This book was released on 2022-10-27 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a detailed introduction to near-sensor and in-sensor computing paradigms, their working mechanisms, development trends and future directions. The authors also provide a comprehensive review of current progress in this area, analyze existing challenges in the field, and offer possible solutions. Readers will benefit from the discussion of computing approaches that intervene in the vicinity of or inside sensory networks to help process data more efficiently, decreasing power consumption and reducing the transfer of redundant data between sensing and processing units. Provides readers with a detailed introduction to the near-sensor and in-sensor computing paradigms; Includes in-depth and comprehensive summaries of the state-of-the-art development in this field; Discusses and compares various neuromorphic sensors and neural networks: Describes integration technology for near-/in-sensor computing; Reveals the relationship between near-/in-sensor computing and other computing paradigms, such as neuromorphic computing, edge computing, intuitive computing, and in-memory computing.

Neural Information Processing

Author : Sabri Arik
Publisher : Springer
ISBN 13 : 3319265555
Total Pages : 710 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Neural Information Processing by : Sabri Arik

Download or read book Neural Information Processing written by Sabri Arik and published by Springer. This book was released on 2015-12-08 with total page 710 pages. Available in PDF, EPUB and Kindle. Book excerpt: The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks.