Reservoir Computing in Material Substrates

Matthew Dale; Julian Francis Miller; Susan Stepney; Martin Albrecht Trefzer

doi:10.1007/978-981-13-1687-6_7

Reservoir Computing in Material Substrates

Matthew Dale, Julian Francis Miller, Susan Stepney, Martin Albrecht Trefzer

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

We overview Reservoir Computing (RC) with physical systems from an Unconventional Computing (UC) perspective. We discuss challenges present in both fields, including encoding and representation, or how to manipulate and read information; ways to search large and complex configuration spaces of physical systems; and what makes a “good” computing substrate.

Original language	English
Title of host publication	Reservoir Computing
Subtitle of host publication	Theory, Physical Implementations, and Applications
Editors	Kohei Nakajima, Ingo Fischer
Publisher	Springer
Pages	141-166
Number of pages	26
ISBN (Electronic)	9789811316876
ISBN (Print)	9789811316869
DOIs	https://doi.org/10.1007/978-981-13-1687-6_7
Publication status	Published - 6 Aug 2021

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10.1007/978-981-13-1687-6_7

Spin Inspired Representations
Stepney, S. (Principal investigator), O'Keefe, S. (Co-investigator), Sebald, A. (Co-investigator) & Trefzer, M. A. (Co-investigator)
EPSRC
1/10/18 → 31/03/22
Project: Research project (funded) › Research

Cite this

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title = "Reservoir Computing in Material Substrates",

abstract = "We overview Reservoir Computing (RC) with physical systems from an Unconventional Computing (UC) perspective. We discuss challenges present in both fields, including encoding and representation, or how to manipulate and read information; ways to search large and complex configuration spaces of physical systems; and what makes a “good” computing substrate.",

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AB - We overview Reservoir Computing (RC) with physical systems from an Unconventional Computing (UC) perspective. We discuss challenges present in both fields, including encoding and representation, or how to manipulate and read information; ways to search large and complex configuration spaces of physical systems; and what makes a “good” computing substrate.

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Reservoir Computing in Material Substrates

Abstract

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Spin Inspired Representations

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