Anzeige
Erschienen in:
2013 | OriginalPaper | Buchkapitel
An Experimental Evaluation of Reservoir Computation for Ambient Assisted Living
verfasst von : Davide Bacciu, Stefano Chessa, Claudio Gallicchio, Alessio Micheli, Paolo Barsocchi
Erschienen in: Neural Nets and Surroundings
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.