Abstract:

We have shown that the theoretical framework of Reservoir Computing (RC) can be applied to in materio computing as a computational layer able to extract exploitable information from physical substrates. However, a physical performance limitation of our current system is the number of interfacing electrodes to the material. We have designed and built a new hardware platform that in- creases the previous 12 electrode system to a 64 multi-purpose electrode system. This extra flexibility allows improved performance.

@inproceedings(Dale2017:UCNC:platform,
  author = "Matthew Dale and Julian F. Miller and Susan Stepney and Martin A. Trefzer",
  title = "Extendible Hardware Platform for Reservoir Computing \emph {in materio}",  
  crossref = "UCNC-2017-p"
)

@proceedings(UCNC-2017-p,
  title = "Poster abstracts, UCNC 2017, Fayetteville, Arkansas, USA",
  booktitle = "Poster abstracts, UCNC 2017, Fayetteville, Arkansas, USA",
  year = 2017
)