Reservoir computing using dynamic memristors for temporal information processing

Reservoir computing systems utilize dynamic reservoirs having short-term memory to project features from the temporal inputs into a high-dimensional feature space. A readout function layer can then effectively analyze the projected features for tasks, such as classification and time-series analysis....

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Veröffentlicht in:Nature communications Jg. 8; H. 1; S. 2204 - 10
Hauptverfasser: Du, Chao, Cai, Fuxi, Zidan, Mohammed A., Ma, Wen, Lee, Seung Hwan, Lu, Wei D.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 19.12.2017
Nature Publishing Group
Nature Portfolio
Schlagworte:
639/166/987
639/925/927/1007
Computer memory
Computing time
Data processing
Handwriting
Handwriting recognition
Humanities and Social Sciences
Information processing
Information systems
Memristors
multidisciplinary
Neural networks
Neurons
Science
Science (multidisciplinary)
Short term memory
Time series
Transfer functions
ISSN:2041-1723, 2041-1723
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Zusammenfassung:Reservoir computing systems utilize dynamic reservoirs having short-term memory to project features from the temporal inputs into a high-dimensional feature space. A readout function layer can then effectively analyze the projected features for tasks, such as classification and time-series analysis. The system can efficiently compute complex and temporal data with low-training cost, since only the readout function needs to be trained. Here we experimentally implement a reservoir computing system using a dynamic memristor array. We show that the internal ionic dynamic processes of memristors allow the memristor-based reservoir to directly process information in the temporal domain, and demonstrate that even a small hardware system with only 88 memristors can already be used for tasks, such as handwritten digit recognition. The system is also used to experimentally solve a second-order nonlinear task, and can successfully predict the expected output without knowing the form of the original dynamic transfer function. Reservoir computing facilitates the projection of temporal input signals onto a high-dimensional feature space via a dynamic system, known as the reservoir. Du et al. realise this concept using metal-oxide-based memristors with short-term memory to perform digit recognition tasks and solve non-linear problems.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-017-02337-y