Spatio-Temporal Sparse Variational Bayes Framework
STSVB recovers block sparse signal using matrix variate gaussian scale mixture parameterized by some scalar random parameters and deterministic matrices to model spatio-temporal correlation.
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stsvb_demo.m: Demo code
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expt_SSVEP_demo.m: Demo code to run stsvb_demo.m on the dataset. For more details of dataset, please refer: Y. Wang, X. Chen, X. Gao and S. Gao, "A Benchmark Dataset for SSVEP-Based Brain–Computer Interfaces," in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 25, no. 10, pp. 1746-1752, Oct. 2017. Dataset is freely available on http://bci.med.tsinghua.edu.cn/download.html.
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my_cca.m : CCA code
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myrefsig.m and genPhi.m : Auxiliary function files to run stsvb_demo.m and expt_SSVEP_demo.m
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Results.mat: File containing details of the results corresponding to Subject 27.
Data