Abstract:
:Novel methods for information processing are highly desired in our information-driven society. Inspired by the brain's ability to process information, the recently introduced paradigm known as 'reservoir computing' shows that complex networks can efficiently perform computation. Here we introduce a novel architecture that reduces the usually required large number of elements to a single nonlinear node with delayed feedback. Through an electronic implementation, we experimentally and numerically demonstrate excellent performance in a speech recognition benchmark. Complementary numerical studies also show excellent performance for a time series prediction benchmark. These results prove that delay-dynamical systems, even in their simplest manifestation, can perform efficient information processing. This finding paves the way to feasible and resource-efficient technological implementations of reservoir computing.
journal_name
Nat Communjournal_title
Nature communicationsauthors
Appeltant L,Soriano MC,Van der Sande G,Danckaert J,Massar S,Dambre J,Schrauwen B,Mirasso CR,Fischer Idoi
10.1038/ncomms1476subject
Has Abstractpub_date
2011-09-13 00:00:00pages
468issn
2041-1723pii
ncomms1476journal_volume
2pub_type
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