Primer to Neuromorphic Computing
Primer to Neuromorphic Computing

Author: Harish Garg

Publisher: Academic Press

Published: 2024-11-01

Total Pages: 0

ISBN-13: 9780443214806

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Primer to Neuromorphic Computing highlights critical and ongoing research into the diverse applications of neuromorphic computing. It includes an overview of primary scientific concepts for the research topic of neuromorphic computing, such as neurons as computational units, artificial intelligence, machine learning, and neuromorphic models. It also discusses the fundamental design method and organization of neuromorphic architecture. Hardware for neuromorphic systems can be developed by exploiting the magnetic properties of different materials. These systems are more energy efficient and enable faster computation . Magnetic tunnel junctions and magnetic textures can be employed to act as neurons and synapses. Neuromorphic systems have general intelligence like humans as they can apply knowledge gained in one domain to other domains.

Handbook of Neural Computing Applications
Handbook of Neural Computing Applications

Author: Alianna J. Maren

Publisher: Academic Press

Published: 2014-05-10

Total Pages: 472

ISBN-13: 148326484X

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Handbook of Neural Computing Applications is a collection of articles that deals with neural networks. Some papers review the biology of neural networks, their type and function (structure, dynamics, and learning) and compare a back-propagating perceptron with a Boltzmann machine, or a Hopfield network with a Brain-State-in-a-Box network. Other papers deal with specific neural network types, and also on selecting, configuring, and implementing neural networks. Other papers address specific applications including neurocontrol for the benefit of control engineers and for neural networks researchers. Other applications involve signal processing, spatio-temporal pattern recognition, medical diagnoses, fault diagnoses, robotics, business, data communications, data compression, and adaptive man-machine systems. One paper describes data compression and dimensionality reduction methods that have characteristics, such as high compression ratios to facilitate data storage, strong discrimination of novel data from baseline, rapid operation for software and hardware, as well as the ability to recognized loss of data during compression or reconstruction. The collection can prove helpful for programmers, computer engineers, computer technicians, and computer instructors dealing with many aspects of computers related to programming, hardware interface, networking, engineering or design.

The 1989 Neuro-computing Bibliography
The 1989 Neuro-computing Bibliography

Author: Casimir C. Klimasauskas

Publisher: MIT Press (MA)

Published: 1989

Total Pages: 648

ISBN-13:

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This comprehensive bibliography provides a functional, flexible tool for researchers and engineers in neurocomputing.

Neuromorphic Photonics
Neuromorphic Photonics

Author: Paul R. Prucnal

Publisher: CRC Press

Published: 2017-05-08

Total Pages: 412

ISBN-13: 1498725244

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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.

Neuromorphic Photonic Devices and Applications
Neuromorphic Photonic Devices and Applications

Author: Min Gu

Publisher: Elsevier

Published: 2023-12-01

Total Pages: 415

ISBN-13: 0323972608

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Neuromorphic Photonic Devices and Applications synthesizes the most critical advances in photonic neuromorphic models, photonic material platforms and accelerators for neuromorphic computing. The book discusses fields and applications that can leverage these new platforms. A brief review of the historical development of the field is followed by a discussion of the emerging 2D photonic materials platforms and recent work in implementing neuromorphic models and 3D neuromorphic systems. The application of artificial intelligence (AI), such as neuromorphic models to inverse design neuromorphic materials and devices and predict performance challenges is discussed throughout. Finally, a comprehensive overview of the applications of neuromorphic photonic technologies and the challenges, opportunities and future prospects is discussed, making the book suitable for researchers and practitioners in academia and R&D in the multidisciplinary field of photonics. - Includes overview of primary scientific concepts for the research topic of neuromorphic photonics such as neurons as computational units, artificial intelligence, machine learning and neuromorphic models - Reviews the latest advances in photonic materials, device platforms and enabling technology drivers of neuromorphic photonics - Discusses potential applications in computing and optical communications

Phase Change Materials-Based Photonic Computing
Phase Change Materials-Based Photonic Computing

Author: Harish Bhaskaran

Publisher: Elsevier

Published: 2024-01-21

Total Pages: 272

ISBN-13: 012823492X

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Phase Change Materials-Based Photonic Computing provides a clear introduction to the field, introducing concepts of photonics, computing, phase change materials and future outlooks. Phase change materials are well known and studied in many contexts, and photonics is a longstanding field, with photonic neuromorphic computing recently gathering interest. However, the two fields are disparate and few people understand the key concepts needed to integrate the two. This book will be the first to do so in this promising field. It is suitable for researchers and practitioners in academia and industry working in the disciplines of materials science and engineering, electrical engineering and computing. - Introduces the advanced fundamental concepts of photonics computing and phase change materials - Reviews the remaining challenges to translation, opportunities and future outlooks - Addresses definitions, historical context, foundational concepts and the latest advances of phase change materials-based photonics computing

Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices
Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices

Author: Manan Suri

Publisher: Springer

Published: 2017-01-21

Total Pages: 217

ISBN-13: 813223703X

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This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The book offers readers a bidirectional (top-down and bottom-up) perspective on designing efficient bio-inspired hardware. At the nanodevice level, it focuses on various flavors of emerging resistive memory (RRAM) technology. At the algorithm level, it addresses optimized implementations of supervised and stochastic learning paradigms such as: spike-time-dependent plasticity (STDP), long-term potentiation (LTP), long-term depression (LTD), extreme learning machines (ELM) and early adoptions of restricted Boltzmann machines (RBM) to name a few. The contributions discuss system-level power/energy/parasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field.

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications
Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications

Author: Christos Volos

Publisher: Academic Press

Published: 2021-06-17

Total Pages: 570

ISBN-13: 0128232021

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Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields. - Covers a broad range of interdisciplinary topics between mathematics, circuits, realizations, and practical applications related to nonlinear dynamical systems, nanotechnology, analog and digital systems, computer science and artificial intelligence - Presents recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) - Includes interesting applications of mem-elements in nonlinear dynamical systems, analog and digital systems, neuromorphic circuits, computer science and artificial intelligence