neuromorphic computing (361 résultats)

Paperback. Etat : new. Paperback. PrefaceIn the ever-evolving landscape of artificial intelligence and computing, neuromorphic computing stands as a beacon of innovation, promising a paradigm shift in how we design and build intelligent machines. For decades, the conventional Von Neumann architecture, while powerful, has grappled with the inherent limitations of separating processing and memory, leading to the infamous "memory wall." Meanwhile, the human brain, an organ of unparalleled complexity and efficiency, effortlessly processes vast amounts of information with remarkable speed and minimal energy consumption. Neuromorphic computing seeks to bridge this gap, drawing profound inspiration from the brain's intricate structure and function to create systems that are not just faster, but fundamentally smarter and more energy-efficient.Purpose of the BookThe primary purpose of "Neuromorphic Computing: Architectures That Think Like Us" is to demystify this exciting and rapidly advancing field. We aim to provide a comprehensive and accessible exploration of neuromorphic computing, from its biological underpinnings to its cutting-edge hardware implementations and diverse applications. This book is designed to serve as a foundational guide for understanding the core principles, the technological advancements, and the immense potential of brain-inspired systems. We will delve into how these architectures are designed to overcome the limitations of traditional computing, enabling new frontiers in AI, robotics, and cognitive modeling. Ultimately, our goal is to empower readers with the knowledge to grasp the significance of this revolution and to contribute to its future.Who Should Read This BookThis book is tailored for a diverse audience, including: Students and Researchers in computer science, electrical engineering, neuroscience, and artificial intelligence who are looking to understand the fundamentals and latest advancements in neuromorphic computing.Engineers and Developers interested in designing and programming brain-inspired hardware and software for real-world applications.AI Practitioners and Enthusiasts curious about the next generation of artificial intelligence and how biological principles are shaping its evolution.Anyone with a keen interest in the intersection of biology, technology, and the future of intelligent systems. Whether you are a seasoned expert or new to the field, this book offers valuable insights and practical knowledge.How to Use This BookThis book is structured to guide you through the complexities of neuromorphic computing in a logical and progressive manner: Part I: Foundations of Neuromorphic Computing lays the groundwork by introducing the core concepts, historical context, and the biological inspirations behind neuromorphic architectures. If you're new to the subject, start here to build a strong conceptual understanding.Part II: Hardware Architectures and Technologies dives deep into the silicon, exploring the leading neuromorphic chips and the emerging technologies that are making these brain-inspired systems a reality. This section is crucial for understanding the physical manifestation of neuromorphic principles.Part III: Algorithms and Learning Mechanisms focuses on the software side, detailing the learning rules and programming frameworks that enable neuromorphic systems to learn and adapt. For those looking to work with or develop for these systems, this part offers essential practical insights.Part IV: Applications and Case Studies showcases the diverse and impactful uses of neuromorphic computing across various domains, from computer vision to robotics and cognitive modeling. These chapters provide real- Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Hardback. Etat : New. Artificial intelligence is transforming industries and society, but its high energy demands challenge global sustainability goals. Biological intelligence, in contrast, offers both good performance and exceptional energy efficiency. Neuromorphic computing, a growing field inspired by the structure and function of the brain, aims to create energy-efficient algorithms and hardware by integrating insights from biology, physics, computer science, and electrical engineering. This concise and accessible book delves into the principles, mechanisms, and properties of neuromorphic systems. It opens with a primer on biological intelligence, describing learning mechanisms in both simple and complex organisms, then turns to the application of these principles and mechanisms in the development of artificial synapses and neurons, circuits, and architectures. The text also delves into neuromorphic algorithm design, and the unique challenges faced by algorithmic researchers working in this area. The book concludes with a selection of practice problems, with solutions available to instructors online.

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Paperback. Etat : new. Paperback. This book delves into the transformative potential of neuromorphic computing within the field of civil engineering, specifically focusing on its application to disaster management. With the increasing frequency and severity of natural disasters, traditional disaster management systems face significant challenges in prediction accuracy, response time, and effective resource allocation. Neuromorphic computing, inspired by the neural processes of the human brain, offers a revolutionary approach to addressing these challenges. Through an in-depth exploration, this book outlines the theoretical foundations of neuromorphic computing, its integration into smart infrastructure, and the development of advanced predictive models for natural disasters such as earthquakes, floods, and urban fires. Additionally, it examines the technical, ethical, and social considerations inherent in deploying these technologies, alongside a vision for their future development. The convergence of neuromorphic computing and civil engineering heralds a new era of enhanced resilience, where more informed, rapid, and effective disaster management strategies are not just a possibility but a reality. The book contributes to the discourse on leveraging cutting-edge computing technologies to foster safer, more resilient communities in the face of natural calamities. This book delves into the transformative potential of neuromorphic computing within the field of civil engineering, specifically focusing on its application to disaster management. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Etat : New. 2022 ed. PRODUCT DESCRIPTION This book focuses on neuromorphic computing principles and organization and how to build fault-tolerant scalable hardware for large and medium scale spiking neural networks with learning capabilities. In addition, the book describes in a comprehensive way the organization and how to design a spike-based neuromorphic system to perform network of spiking neurons communication, computing, and adaptive learning for emerging AI applications. The book begins with an overview of neuromorphic computing systems and explores the fundamental concepts of artificial neural networks. Next, we discuss artificial neurons and how they have evolved in their representation of biological neuronal dynamics. Afterward, we discuss implementing these neural networks in neuron models, storage technologies, inter-neuron communication networks, learning, and various design approaches. Then, comes the fundamental design principle to build an efficient neuromorphic system in hardware. The challenges that need to be solved toward building a spiking neural network architecture with many synapses are discussed. Learning in neuromorphic computing systems and the major emerging memory technologies that promise neuromorphic computing are then given.A particular chapter of this book is dedicated to the circuits and architectures used for communication in neuromorphic systems. In particular, the Network-on-Chip fabric is introduced for receiving and transmitting spikes following the Address Event Representation (AER) protocol and the memory accessing method. In addition, the interconnect design principle is covered to help understand the overall concept of on-chip and off-chip communication. Advanced on-chip interconnect technologies, including si-photonic three-dimensional interconnects and fault-tolerant routing algorithms, are also given. The book also covers the main threats of reliability and discusses several recovery methods for multicore neuromorphic systems. This is important for reliable processing in several embedded neuromorphic applications. A reconfigurable design approach that supports multiple target applications via dynamic reconfigurability, network topology independence, and network expandability is also described in the subsequent chapters. The book ends with a case study about a real hardware-software design of a reliable three-dimensional digital neuromorphic processor geared explicitly toward the 3D-ICs biological brain's three-dimensional structure. The platform enables high integration density and slight spike delay of spiking networks and features a scalable design. We present methods for fault detection and recovery in a neuromorphic system as well.Neuromorphic Computing Principles and Organization is an excellent resource for researchers, scientists, graduate students, and hardware-software engineers dealing with the ever-increasing demands on fault-tolerance, scalability, and low power consumption. It is also an excellent resource fo.

Paperback. Etat : new. Paperback. PrefaceIn the ever-evolving landscape of artificial intelligence and computing, neuromorphic computing stands as a beacon of innovation, promising a paradigm shift in how we design and build intelligent machines. For decades, the conventional Von Neumann architecture, while powerful, has grappled with the inherent limitations of separating processing and memory, leading to the infamous "memory wall." Meanwhile, the human brain, an organ of unparalleled complexity and efficiency, effortlessly processes vast amounts of information with remarkable speed and minimal energy consumption. Neuromorphic computing seeks to bridge this gap, drawing profound inspiration from the brain's intricate structure and function to create systems that are not just faster, but fundamentally smarter and more energy-efficient.Purpose of the BookThe primary purpose of "Neuromorphic Computing: Architectures That Think Like Us" is to demystify this exciting and rapidly advancing field. We aim to provide a comprehensive and accessible exploration of neuromorphic computing, from its biological underpinnings to its cutting-edge hardware implementations and diverse applications. This book is designed to serve as a foundational guide for understanding the core principles, the technological advancements, and the immense potential of brain-inspired systems. We will delve into how these architectures are designed to overcome the limitations of traditional computing, enabling new frontiers in AI, robotics, and cognitive modeling. Ultimately, our goal is to empower readers with the knowledge to grasp the significance of this revolution and to contribute to its future.Who Should Read This BookThis book is tailored for a diverse audience, including: Students and Researchers in computer science, electrical engineering, neuroscience, and artificial intelligence who are looking to understand the fundamentals and latest advancements in neuromorphic computing.Engineers and Developers interested in designing and programming brain-inspired hardware and software for real-world applications.AI Practitioners and Enthusiasts curious about the next generation of artificial intelligence and how biological principles are shaping its evolution.Anyone with a keen interest in the intersection of biology, technology, and the future of intelligent systems. Whether you are a seasoned expert or new to the field, this book offers valuable insights and practical knowledge.How to Use This BookThis book is structured to guide you through the complexities of neuromorphic computing in a logical and progressive manner: Part I: Foundations of Neuromorphic Computing lays the groundwork by introducing the core concepts, historical context, and the biological inspirations behind neuromorphic architectures. If you're new to the subject, start here to build a strong conceptual understanding.Part II: Hardware Architectures and Technologies dives deep into the silicon, exploring the leading neuromorphic chips and the emerging technologies that are making these brain-inspired systems a reality. This section is crucial for understanding the physical manifestation of neuromorphic principles.Part III: Algorithms and Learning Mechanisms focuses on the software side, detailing the learning rules and programming frameworks that enable neuromorphic systems to learn and adapt. For those looking to work with or develop for these systems, this part offers essential practical insights.Part IV: Applications and Case Studies showcases the diverse and impactful uses of neuromorphic computing across various domains, from computer vision to robotics and cognitive modeling. These chapters Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Etat : new. Hardcover. This book explores the reliability and security challenges of Computing-in-Memory (CIM), a promising approach to overcoming the limitations of traditional computing. It examines the weaknesses of memristive devices, which are key to this technology, and presents practical methods to improve their stability and security. Key topics include a fault injection platform for testing reliability, the NeuroHammer attack, which exposes security risks, and the NeuroBreakoutBoard, a hardware tool for evaluating real devices. By bridging theory and practice, this book is essential for researchers, engineers, and industry professionals working on next-generation computing systems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Etat : new. Paperback. This book focuses on neuromorphic computing principles and organization and how to build fault-tolerant scalable hardware for large and medium scale spiking neural networks with learning capabilities. In addition, the book describes in a comprehensive way the organization and how to design a spike-based neuromorphic system to perform network of spiking neurons communication, computing, and adaptive learning for emerging AI applications. The book begins with an overview of neuromorphic computing systems and explores the fundamental concepts of artificial neural networks. Next, we discuss artificial neurons and how they have evolved in their representation of biological neuronal dynamics. Afterward, we discuss implementing these neural networks in neuron models, storage technologies, inter-neuron communication networks, learning, and various design approaches. Then, comes the fundamental design principle to build an efficient neuromorphic system in hardware. The challenges that needto be solved toward building a spiking neural network architecture with many synapses are discussed. Learning in neuromorphic computing systems and the major emerging memory technologies that promise neuromorphic computing are then given.A particular chapter of this book is dedicated to the circuits and architectures used for communication in neuromorphic systems. In particular, the Network-on-Chip fabric is introduced for receiving and transmitting spikes following the Address Event Representation (AER) protocol and the memory accessing method. In addition, the interconnect design principle is covered to help understand the overall concept of on-chip and off-chip communication. Advanced on-chip interconnect technologies, including si-photonic three-dimensional interconnects and fault-tolerant routing algorithms, are also given. The book also covers the main threats of reliability and discusses several recovery methods for multicore neuromorphic systems. This is important for reliable processing in several embedded neuromorphic applications. A reconfigurable design approach that supports multiple target applications via dynamic reconfigurability, network topology independence, and network expandability is also described in the subsequent chapters. The book ends with a case study about a real hardware-software design of a reliable three-dimensional digital neuromorphic processor geared explicitly toward the 3D-ICs biological brains three-dimensional structure. The platform enables high integration density and slight spike delay of spiking networks and features a scalable design. We present methods for fault detection and recovery in a neuromorphic system as well.Neuromorphic Computing Principles and Organization is an excellent resource for researchers, scientists, graduate students, and hardware-software engineers dealing with the ever-increasing demands on fault-tolerance, scalability, and low power consumption. It is also an excellent resource for teaching advanced undergraduate and graduate students about the fundamentals concepts, organization, and actual hardware-software design of reliable neuromorphic systems with learning and fault-tolerance capabilities. This book focuses on neuromorphic computing principles and organization and how to build fault-tolerant scalable hardware for large and medium scale spiking neural networks with learning capabilities. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Etat : New. 2022 ed. PRODUCT DESCRIPTION This book focuses on neuromorphic computing principles and organization and how to build fault-tolerant scalable hardware for large and medium scale spiking neural networks with learning capabilities. In addition, the book describes in a comprehensive way the organization and how to design a spike-based neuromorphic system to perform network of spiking neurons communication, computing, and adaptive learning for emerging AI applications. The book begins with an overview of neuromorphic computing systems and explores the fundamental concepts of artificial neural networks. Next, we discuss artificial neurons and how they have evolved in their representation of biological neuronal dynamics. Afterward, we discuss implementing these neural networks in neuron models, storage technologies, inter-neuron communication networks, learning, and various design approaches. Then, comes the fundamental design principle to build an efficient neuromorphic system in hardware. The challenges that need to be solved toward building a spiking neural network architecture with many synapses are discussed. Learning in neuromorphic computing systems and the major emerging memory technologies that promise neuromorphic computing are then given.A particular chapter of this book is dedicated to the circuits and architectures used for communication in neuromorphic systems. In particular, the Network-on-Chip fabric is introduced for receiving and transmitting spikes following the Address Event Representation (AER) protocol and the memory accessing method. In addition, the interconnect design principle is covered to help understand the overall concept of on-chip and off-chip communication. Advanced on-chip interconnect technologies, including si-photonic three-dimensional interconnects and fault-tolerant routing algorithms, are also given. The book also covers the main threats of reliability and discusses several recovery methods for multicore neuromorphic systems. This is important for reliable processing in several embedded neuromorphic applications. A reconfigurable design approach that supports multiple target applications via dynamic reconfigurability, network topology independence, and network expandability is also described in the subsequent chapters. The book ends with a case study about a real hardware-software design of a reliable three-dimensional digital neuromorphic processor geared explicitly toward the 3D-ICs biological brain's three-dimensional structure. The platform enables high integration density and slight spike delay of spiking networks and features a scalable design. We present methods for fault detection and recovery in a neuromorphic system as well.Neuromorphic Computing Principles and Organization is an excellent resource for researchers, scientists, graduate students, and hardware-software engineers dealing with the ever-increasing demands on fault-tolerance, scalability, and low power consumption. It is also an excellent resource fo.

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