- 中图分类号: TN
- 语种: ENG
- 出版信息: Wiley 2014 442页
- EISBN: 9781118927632
- PISBN-P: 9780470018491
- 原文访问地址:
KG评星
知识图谱评星,是一种基于用户使用的评价体系,综合图书的评论数量、引文数量、Amazon评分以及图谱网络中节点的PageRank值(即考虑相邻节点数量和重要性)等多种因素计算而得出的评价数值。星级越高,推荐值越高。CAT核心级
核心学术资源(CAR)项目作为教图公司推出的一项知识型服务,旨在打造一套科学、有效的图书评价体系,并协助用户制定相应的馆藏建设方案。CAR项目调查和分析12所世界一流大学的藏书数据,以收藏学校的数量确定书目的核心级,核心级越高,代表书目的馆藏价值越高。选取核心级在三级以上,即三校以上共藏的图书作为核心书目(CAT)。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. This cross-disciplinary text establishes how circuit building blocks are combined in architectures to construct complete systems. These include vision and auditory sensors as well as neuronal processing and learning circuits that implement models of nervous systems. Techniques for building multi-chip scalable systems are considered throughout the book, including methods for dealing with transistor mismatch, extensive discussions of communication and interfacing, and making systems that operate in the real world. The book also provides historical context that helps relate the architectures and circuits to each other and that guides readers to the extensive literature. Chapters are written by founding experts and have been extensively edited for overall coherence. This pioneering text is an indispensable resource for practicing neuromorphic electronic engineers, advanced electrical engineering and computer science students and researchers interested in neuromorphic systems. Key features: Summarises the latest design approaches, applications, and future challenges in the field of neuromorphic engineering. Presents examples of practical applications of neuromorphic design principles. Covers address-event communication, retinas, cochleas, locomotion, learning theory, neurons, synapses, floating gate circuits, hardware and software infrastructure, algorithms, and future challenges.