Biologically-Inspired Neuromorphic Computing

被引:4
|
作者
Olin-Ammentorp, Wilkie [1 ]
Cady, Nathaniel [1 ]
机构
[1] SUNY Polytech Inst, Coll Nanoscale Sci & Engn, 257 Fuller Rd, Albany, NY 12203 USA
关键词
Neuromorphic; spiking neural networks; neuromorphic engineering; emerging technology; computation; post-Moore's law; CORTICAL-NEURONS; COMPUTATION; NETWORKS; NOISE; MODEL;
D O I
10.1177/0036850419850394
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Advances in integrated circuitry from the 1950s to the present day have enabled a revolution in technology across the world. However, fundamental limits of circuitry make further improvements through historically successful methods increasingly challenging. It is becoming clear that to address new challenges and applications, new methods of computation will be required. One promising field is neuromorphic engineering, a broad field which applies biologically inspired principles to create alternative computational architectures and methods. We address why neuromorphic engineering is one of the most promising fields within emerging computational technology, elaborating on its common principles and models, and discussing its current state and future challenges.
引用
收藏
页码:261 / 276
页数:16
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