Physical reservoir computing -- An introductory perspective
- URL: http://arxiv.org/abs/2005.00992v1
- Date: Sun, 3 May 2020 05:39:06 GMT
- Title: Physical reservoir computing -- An introductory perspective
- Authors: Kohei Nakajima
- Abstract summary: Physical reservoir computing allows one to exploit the complex dynamics of physical systems as information-processing devices.
This paper aims to illustrate the potentials of the framework using examples from soft robotics.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Understanding the fundamental relationships between physics and its
information-processing capability has been an active research topic for many
years. Physical reservoir computing is a recently introduced framework that
allows one to exploit the complex dynamics of physical systems as
information-processing devices. This framework is particularly suited for edge
computing devices, in which information processing is incorporated at the edge
(e.g., into sensors) in a decentralized manner to reduce the adaptation delay
caused by data transmission overhead. This paper aims to illustrate the
potentials of the framework using examples from soft robotics and to provide a
concise overview focusing on the basic motivations for introducing it, which
stem from a number of fields, including machine learning, nonlinear dynamical
systems, biological science, materials science, and physics.
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