2012
Report
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An Experimental Evaluation of Reservoir Computation for Ambient Assisted Living.
Bacciu D., Barsocchi P., Chessa S., Gallicchio C., Micheli A.
Ambient Assisted Living
In this paper we investigate the introduction of Reservoir Computing (RC) neural network models in the context of AAL (Ambient Assisted Living) and self-learning robot ecologies, with a focus on the computational constraints related to the implementation over a network of sensors. Specifically, we experimentally study the relationship between architectural parameters influencing the computational cost of the models and the performance on a task of user movements prediction from sensors signal streams. The RC shows favorable scaling properties results for the analyzed AAL task.
Source: ISTI Technical reports, pp.1–10, 2012
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BibTeX entry
@techreport{oai:it.cnr:prodotti:213911,
title = {An Experimental Evaluation of Reservoir Computation for Ambient Assisted Living.},
author = {Bacciu D. and Barsocchi P. and Chessa S. and Gallicchio C. and Micheli A.},
institution = {ISTI Technical reports, pp.1–10, 2012},
year = {2012}
}CNR authorsLaboratories
0000-0002-6862-7593CNR ExploRA
