Brain state decoding based on fmri using semisupervised sparse representation classifications

HIGHLIGHTS

  • who: Jing Zhang and collaborators from the State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China have published the paper: Brain State Decoding Based on fMRI Using Semisupervised Sparse Representation Classifications, in the Journal: Computational Intelligence and Neuroscience of 19/04/2018
  • what: Based on the updating criterion, the authors propose the semisupervised SRCAVE (semiSRC-AVE) algorithm that combines self-training and SRC-AVE. This study proposed the semisupervised learning semiSRC-AVE method to improve the decoding performance of SRC. The authors demonstrated the . . .

     

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