Evolving Spiking Neural Networks for online learning over drifting data streams

Nowadays huge volumes of data are produced in the form of fast streams, which are further affected by non-stationary phenomena. The resulting lack of stationarity in the distribution of the produced data calls for efficient and scalable algorithms for online analysis capable of adapting to such chan...

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Veröffentlicht in:	Neural networks 2018-12, Vol.108, p.1-19
Hauptverfasser:	Lobo, Jesus L., Laña, Ibai, Del Ser, Javier, Bilbao, Miren Nekane, Kasabov, Nikola
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Concept drift Data reduction Education, Distance - trends Humans Models, Neurological Neural Networks (Computer) Neurons - physiology Online learning Spiking Neural Networks
Online-Zugang:	Volltext
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