SSVEP unsupervised adaptive feature recognition method based on self-similarity of same-frequency signals

SSVEP unsupervised adaptive feature recognition method based on self-similarity of same-frequency signals

IntroductionAs an important human-computer interaction technology, steady-state visual evoked potential (SSVEP) plays a key role in the application of brain computer interface (BCI) systems by accurately decoding SSVEP signals. Currently, the majority SSVEP feature recognition methods use a static c...

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Bibliographic Details
Main Authors: Wenqiang Yan, Bo He, Jin Zhao
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-08-01
Series:Frontiers in Neuroscience
Subjects:
steady-state visual evoked potential
brain-computer interface
unsupervised adaptive classification algorithm
co-frequency self-similarity
signal detection
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2023.1161511/full

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https://www.frontiersin.org/articles/10.3389/fnins.2023.1161511/full

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