Towards reservoir computing with autonomous Boolean networks

Abstract : We present our preliminary work developing a reservoir computing platform using field-programmable gate arrays (FPGAs), with the ultimate goal of detecting features of complex systems. We show that the three basic properties required for reservoir computing, namely that different input states are mapped to different reservoir states, input states that are close together are mapped to identical reservoir states, and a fading memory, can be realized even in moderately-sized Boolean networks synthesized on an FPGA. The networks are realized as ring oscillators consisting of multiple-input XOR gates that accept an input (Boolean) voltage and time-delayed feedback. These oscillators exhibit long chaotic transients when the input voltage is flipped, and it is found that these transients offer promising dynamics for reservoir computing.
Type de document :
Poster
33rd meeting of Dynamics Days US 2014, Jan 2014, Atlanta, United States. 2014
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https://hal-supelec.archives-ouvertes.fr/hal-01109808
Contributeur : Sébastien Van Luchene <>
Soumis le : mardi 27 janvier 2015 - 09:43:45
Dernière modification le : jeudi 5 avril 2018 - 12:30:21

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  • HAL Id : hal-01109808, version 1

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Nicholas D. Haynes, David P. Rosin, Damien Rontani, Daniel J. Gauthier. Towards reservoir computing with autonomous Boolean networks. 33rd meeting of Dynamics Days US 2014, Jan 2014, Atlanta, United States. 2014. 〈hal-01109808〉

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