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Building Neuromorphic Circuits with Memristive Devices

机译:用忆阻器件构建神经形态电路

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摘要

The rapid, exponential growth of modern electronics has brought about profound changes to our daily lives. However, maintaining the growth trend now faces significant challenges at both the fundamental and practical levels [1]. Possible solutions include More Moore?developing new, alternative device structures and materials while maintaining the same basic computer architecture, and More Than Moore?enabling alternative computing architectures and hybrid integration to achieve increased system functionality without trying to push the devices beyond limits. In particular, an increasing number of computing tasks today are related to handling large amounts of data, e.g. image processing as an example. Conventional von Neumann digital computers, with separate memory and processer units, become less and less efficient when large amount of data have to be moved around and processed quickly. Alternative approaches such as bio-inspired neuromorphic circuits, with distributed computing and localized storage in networks, become attractive options [2]?[6].
机译:现代电子技术的快速,指数增长为我们的日常生活带来了深刻的变化。然而,保持增长趋势目前在基本和实际层面都面临着重大挑战[1]。可能的解决方案包括:More Moore在维持相同的基本计算机体系结构的同时开发新的替代设备结构和材料,以及More Than Moore在替代性计算体系结构和混合集成的情况下实现增加的系统功能,而又不试图将设备推向极限。特别地,当今越来越多的计算任务与处理大量数据有关,例如,处理大量数据。以图像处理为例。当必须快速移动和处理大量数据时,具有单独的内存和处理器单元的常规冯·诺依曼数字计算机的效率越来越低。诸如生物启发式神经形态电路之类的替代方法,具有分布式计算和网络中的本地存储,已成为有吸引力的选择[2]→[6]。

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  • 来源
    《IEEE circuits and systems magazine》 |2013年第2期|56-73|共18页
  • 作者

    Chang T.; Yang Y.; Lu W.;

  • 作者单位

    Electrical Engineering and Computer Science, University of Michigan ?? Ann Arbor, Ann Arbor, Michigan 48109 USA|c|;

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  • 正文语种 eng
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  • 入库时间 2022-08-17 14:02:25

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