Step-like dependence of memory function on pulse width in spintronics reservoir computing.

ABSTRACT: Physical reservoir computing is a type of recurrent neural network that applies the dynamical response from physical systems to information processing. However, the relation between computation performance and physical parameters/phenomena still remains unclear. This study reports our progress regarding the role of current-dependent magnetic damping in the computational performance of reservoir computing. The current-dependent relaxation dynamics of a magnetic vortex core results in an asymmetric memory function with respect to binary inputs. A fast relaxation caused by a large input leads to a fast fading of the input memory, whereas a slow relaxation by a small input enables the reservoir to keep the input memory for a relatively long time. As a result, a step-like dependence is found fo

SUBMITTER: Yamaguchi T 

PROVIDER: S-EPMC7659325 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature