Literature DB >> 32006747

Performance boost of time-delay reservoir computing by non-resonant clock cycle.

Florian Stelzer1, André Röhm2, Kathy Lüdge3, Serhiy Yanchuk4.   

Abstract

The time-delay-based reservoir computing setup has seen tremendous success in both experiment and simulation. It allows for the construction of large neuromorphic computing systems with only few components. However, until now the interplay of the different timescales has not been investigated thoroughly. In this manuscript, we investigate the effects of a mismatch between the time-delay and the clock cycle for a general model. Typically, these two time scales are considered to be equal. Here we show that the case of equal or resonant time-delay and clock cycle could be actively detrimental and leads to an increase of the approximation error of the reservoir. In particular, we can show that non-resonant ratios of these time scales have maximal memory capacities. We achieve this by translating the periodically driven delay-dynamical system into an equivalent network. Networks that originate from a system with resonant delay-times and clock cycles fail to utilize all of their degrees of freedom, which causes the degradation of their performance.
Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Clock cycle; Memory capacity; Network representation; Reservoir computing; Resonance; Time-delay

Mesh:

Year:  2020        PMID: 32006747     DOI: 10.1016/j.neunet.2020.01.010

Source DB:  PubMed          Journal:  Neural Netw        ISSN: 0893-6080


  3 in total

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Journal:  Sci Rep       Date:  2022-03-08       Impact factor: 4.996

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  3 in total

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