Brain Inspired Computing From Neuroscience To Neuromorphic Electronics Driving New Forms Of Artificial Intelligence

Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence In Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics, a team of expert engineers delivers a comprehensive discussion of all aspects of neuromorphic electronics designed to assist researchers and professionals to understand and apply all manner of brain-inspired computing and perception technologies. The book covers both memristic and neuromorphic devices, including spintronic, multi-terminal, and neuromorphic perceptual applications. Summarizing recent progress made in five distinct configurations of brain-inspired computing, the authors explore this promising technology’s potential applications in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. The book also includes: A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors Practical discussions of neuromorphic devices based on chalcogenide and organic materials In-depth examinations of neuromorphic computing and perceptual systems with emerging devices Perfect for materials scientists, biochemists, and electronics engineers, Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.

It is generally understood that the present approachs to computing do not have the performance, flexibility, and reliability of biological information processing systems. Although there is a comprehensive body of knowledge regarding how information processing occurs in the brain and central nervous system this has had little impact on mainstream computing so far. This book presents a broad spectrum of current research into biologically inspired computational systems and thus contributes towards developing new computational approaches based on neuroscience. The 39 revised full papers by leading researchers were carefully selected and reviewed for inclusion in this anthology. Besides an introductory overview by the volume editors, the book offers topical parts on modular organization and robustness, timing and synchronization, and learning and memory storage.

Dive into the cutting-edge world of Neuromorphic Computing, a groundbreaking volume that unravels the secrets of brain-inspired computational paradigms. Spanning neuroscience, artificial intelligence, and hardware design, this book presents a comprehensive exploration of neuromorphic systems, empowering both experts and newcomers to embrace the limitless potential of brain-inspired computing. Discover the fundamental principles that underpin neural computation as we journey through the origins of neuromorphic architectures, meticulously crafted to mimic the brain’s intricate neural networks. Unlock the true essence of learning mechanisms – unsupervised, supervised, and reinforcement learning – and witness how these innovations are shaping the future of artificial intelligence.

This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.

The brain is not a glorified digital computer. It does not store information in registers, and it does not mathematically transform mental representations to establish perception or behavior. The brain cannot be downloaded to a computer to provide immortality, nor can it destroy the world by having its emerged consciousness traveling in cyberspace. However, studying the brain's core computation architecture can inspire scientists, computer architects, and algorithm designers to think fundamentally differently about their craft. Neuromorphic engineers have the ultimate goal of realizing machines with some aspects of cognitive intelligence. They aspire to design computing architectures that could surpass existing digital von Neumann-based computing architectures' performance. In that sense, brain research bears the promise of a new computing paradigm. As part of a complete cognitive hardware and software ecosystem, neuromorphic engineering opens new frontiers for neuro-robotics, artificial intelligence, and supercomputing applications. This book will present neuromorphic engineering from three perspectives: the scientist, the computer architect, and the algorithm designer. We will zoom in and out of the different disciplines, allowing readers with diverse backgrounds to understand and appreciate the field. Overall, the book will cover the basics of neuronal modeling, neuromorphic circuits, neural architectures, event-based communication, and the neural engineering framework. Readers will have the opportunity to understand the different views over the inherently multidisciplinary field of neuromorphic engineering.

This book constitutes the thoroughly refereed conference proceedings of the International Workshop on Brain-inspired Computing, BrainComp 2013, held in Cetraro, Italy, in July 2013. The 16 revised full papers were carefully reviewed and selected from numerous submissions and cover topics such as brain structure and function as a neuroscience perspective, computational models and brain-inspired computing, HPC and visualization for human brain simulations.