Fundamentals of Organic Neuromorphic Systems, Erokhin Victor
Автор: Shih?€“Chii Liu,Tobi Delbruck,Giacomo Indiveri,Adr Название: Event?€“Based Neuromorphic Systems ISBN: 0470018496 ISBN-13(EAN): 9780470018491 Издательство: Wiley Рейтинг: Цена: 13456.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Neuromorphic electronic engineering takes its inspiration from the functioning of nervous systems to build more power efficient electronic sensors and processors. Event-based neuromorphic systems are inspired by the brain`s efficient data-driven communication design, which is key to its quick responses and remarkable capabilities.
Автор: Pinaki Mazumder; Yalcin Yilmaz Название: Neuromorphic Circuits for Nanoscale Devices ISBN: 8770220603 ISBN-13(EAN): 9788770220606 Издательство: Taylor&Francis Рейтинг: Цена: 14851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Nanoscale devices attracted significant research effort from the industry and academia due to their operation principals being based on different physical properties which provide advantages in the design of certain classes of circuits over conventional CMOS transistors.
Neuromorphic Circuits for Nanoscale Devices contains recent research papers presented in various international conferences and journals to provide insight into how the operational principles of the nanoscale devices can be utilized for the design of neuromorphic circuits for various applications of non-volatile memory, neural network training/learning, and image processing.
Table of Content:
Introduction; 1. Crossbar Memory Simulation and Performance Evaluation; 2. Memristor Digital Memory; 3. Multi-Level Memory Architecture; 4. Neuromorphic Building Blocks with Memristors; 5. Value Iteration with Memristors; 6. 2-D Array of Multi-Peak Resonant Tunneling Diodes Based Color Image Processing; 7. Color Image Processing with Multi-Peak Resonant Tunneling Diodes; 8. Design of a Velocity-Tuned Filter Using a Matrix of Resonant Tunneling Diodes; 9. Image Processing by a Programmable Artificial Retina Comprising Quantum Dots
Автор: Nan Zheng, Pinaki Mazumder Название: Learning in Energy–Efficient Neuromorphic Computing ISBN: 1119507383 ISBN-13(EAN): 9781119507383 Издательство: Wiley Рейтинг: Цена: 15990.00 р. Наличие на складе: Поставка под заказ.
Описание:
Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications
This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities--and provides co-design and co-optimization methodologies for building hardware neural networks that can learn. Presenting a complete picture from high-level algorithm to low-level implementation details, Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design also covers many fundamentals and essentials in neural networks (e.g., deep learning), as well as hardware implementation of neural networks.
The book begins with an overview of neural networks. It then discusses algorithms for utilizing and training rate-based artificial neural networks. Next comes an introduction to various options for executing neural networks, ranging from general-purpose processors to specialized hardware, from digital accelerator to analog accelerator. A design example on building energy-efficient accelerator for adaptive dynamic programming with neural networks is also presented. An examination of fundamental concepts and popular learning algorithms for spiking neural networks follows that, along with a look at the hardware for spiking neural networks. Then comes a chapter offering readers three design examples (two of which are based on conventional CMOS, and one on emerging nanotechnology) to implement the learning algorithm found in the previous chapter. The book concludes with an outlook on the future of neural network hardware.
Includes cross-layer survey of hardware accelerators for neuromorphic algorithms
Covers the co-design of architecture and algorithms with emerging devices for much-improved computing efficiency
Focuses on the co-design of algorithms and hardware, which is especially critical for using emerging devices, such as traditional memristors or diffusive memristors, for neuromorphic computing
Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design is an ideal resource for researchers, scientists, software engineers, and hardware engineers dealing with the ever-increasing requirement on power consumption and response time. It is also excellent for teaching and training undergraduate and graduate students about the latest generation neural networks with powerful learning capabilities.
Автор: Qiang Yu; Huajin Tang; Jun Hu; Kay Tan Chen Название: Neuromorphic Cognitive Systems ISBN: 3319856251 ISBN-13(EAN): 9783319856254 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents neuromorphic cognitive systems from a learning and memory-centered perspective.
Автор: Qiang Yu; Huajin Tang; Jun Hu; Kay Tan Chen Название: Neuromorphic Cognitive Systems ISBN: 3319553089 ISBN-13(EAN): 9783319553085 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents neuromorphic cognitive systems from a learning and memory-centered perspective.
Автор: Tor Sverre Lande Название: Neuromorphic Systems Engineering ISBN: 1475782985 ISBN-13(EAN): 9781475782981 Издательство: Springer Рейтинг: Цена: 26122.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Neuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological neural systems, which are used as inspiration for building large electronic systems in silicon. By adequate engineering, these silicon systems are made useful to mankind. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the reader with a snapshot of neuromorphic engineering today. It is organized into five parts viewing state-of-the-art developments within neuromorphic engineering from different perspectives. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the first collection of neuromorphic systems descriptions with firm foundations in silicon. Topics presented include:
large scale analog systems in silicon
neuromorphic silicon
auditory (ear) and vision (eye) systems in silicon
learning and adaptation in silicon
merging biology and technology
micropower analog circuit design
analog memory
analog interchipcommunication on digital buses /LIST Neuromorphic Systems Engineering: Neural Networks in Silicon serves as an excellent resource for scientists, researchers and engineers in this emerging field, and may also be used as a text for advanced courses on the subject.
Автор: Christoph Rasche Название: The Making of a Neuromorphic Visual System ISBN: 146149849X ISBN-13(EAN): 9781461498490 Издательство: Springer Рейтинг: Цена: 22201.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 1: Seeing: Blazing Processing Characteristics 1.1 An Infinite Reservoir of Information 1.2 Speed 1.3 Illusions 1.4 Recognition Evolvement 1.5 Basic-Level Categorization 1.6 Memory Capacity and Access 1.7 Summary 2: Category Representation and Recognition Evolvement 2.1 Structural Variability Independence 2.2 Viewpoint Independence 2.3 Representation and Evolvement 2.4 Recapitulation 2.5 Refining the Primary Engineering Goal 3: Neuroscientific Inspiration 3.1 Hierarchy and Models 3.2 Criticism and Variants 3.3 Speed 3.4 Alternative 'Codes' 3.5 Alternative Shape Recognition 3.6 Insight from Cases of Visual Agnosia 3 7 Neuronal Level 3.8 Recapitulation and Conclusion 4: Neuromorphic Tools 4.1 The Transistor 4.2 A Synaptic Circuit 4.3 Dendritic Compartments 4.4 An Integrate-and-Fire Neuron 4.5 A Silicon Cortex 4.6 Fabrication Vagrancies require Simplest Models 4.7 Recapitulation 5: Insight From Line Drawings Studies 5.1 A Representation with Polygons 5.2 A Representation with Polygons and their Context 5.3 Recapitulation 6: Retina Circuits Signaling and Propagating Contours 6.1 The Input: a Luminance Landscape 6.2 Spatial Analysis in the Real Retina 6.3 The Propagation Map 6.4 Signaling Contours in Gray-Scale Images 6.5 Recapitulation 7: The Symmetric-Axis Transform 7.1 The Transform 7.2 Architecture 7.3 Performance 7.4 SAT Variants 7.5 Fast Waves 7.6 Recapitulation 8: Motion Detection 8.1 Models 8.2 Speed Detecting Architectures 8.3 Simulation 8.4 Biophysical Plausibility 8.5 Recapitulation 9: Neuromorphic Architectures: Pieces and Proposals 9.1 Integration Perspectives 9.2 Position and Size Invariance 9.3 Architecture for a Template Approach 9.4 Basic-Level Representations 9.5 Recapitulation 10: Shape Recognition with ContourPropagation Fields 10.1 The Idea of the Contour Propagation Field 10.2 Architecture 10.3 Testing 10.4 Discussion 10.5 Learning 10.6 Recapitulation 11: Scene Recognition 11.1 Objects in Scenes, Scene Regularity 11.2 Representation, Evolvement, Gist 11.3 Scene Exploration 11.4 Engineering 11.5 Recapitulation 12: Summary 12.1 The Quest for Efficient Representation and Evolvement 12.2 Contour Extraction and Grouping 12.3 Neuroscientific Inspiration 12.4 Neuromorphic Implementation 12.5 Future Approach Terminology References Index Keywords Abbreviations
Photo-Electroactive Non-Volatile Memories for Data Storage and Neuromorphic Computing summarizes advances in the development of photo-electroactive memories and neuromorphic computing systems, suggests possible solutions to the challenges of device design, and evaluates the prospects for commercial applications. Sections covers developments in electro-photoactive memory, and photonic neuromorphic and in-memory computing, including discussions on design concepts, operation principles and basic storage mechanism of optoelectronic memory devices, potential materials from organic molecules, semiconductor quantum dots to two-dimensional materials with desirable electrical and optical properties, device challenges, and possible strategies.
This comprehensive, accessible and up-to-date book will be of particular interest to graduate students and researchers in solid-state electronics. It is an invaluable systematic introduction to the memory characteristics, operation principles and storage mechanisms of the latest reported electro-photoactive memory devices.
Reviews the most promising materials to enable emerging computing memory and data storage devices, including one- and two-dimensional materials, metal oxides, semiconductors, organic materials, and more
Discusses fundamental mechanisms and design strategies for two- and three-terminal device structures
Addresses device challenges and strategies to enable translation of optical and optoelectronic technologies
Автор: Krichmar Jeffrey L., Wagatsuma Hiroaki Название: Neuromorphic and Brain-Based Robots ISBN: 1108826202 ISBN-13(EAN): 9781108826204 Издательство: Cambridge University Press Рейтинг: Цена: 12507.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Providing an introduction to recent advances in neuromorphic and brain-based robotics, this book explores how robots can be used to better understand the brain. It considers their use in studying how the nervous system gives rise to complex behavior and how this knowledge could be used to develop intelligent robots.
Описание: This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices.
Описание: This book discusses and compares several new trends that can be used to overcome Moore`s law limitations, including Neuromorphic, Approximate, Parallel, In Memory, and Quantum Computing.
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