Unsupervised Hebbian learning experimentally realized with analogue memristive crossbar arrays.

ABSTRACT: Conventional transistor electronics are reaching their limits in terms of scalability, power dissipation, and the underlying Boolean system architecture. To overcome this obstacle neuromorphic analogue systems are recently highly investigated. Particularly, the use of memristive devices in VLSI analogue concepts provides a promising pathway to realize novel bio-inspired computing architectures, which are able to unravel the foreseen difficulties of traditional electronics. Currently, a variety of materials and device structures are being studied along with novel computing schemes to make use of the attractive features of memristive devices for neuromorphic computing. However, a number of obstacles still have to be overcome to cast memristive devices into hardware systems. Most important is

SUBMITTER: Hansen M 

PROVIDER: S-EPMC5995917 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature