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A Hybrid Brain-Computer Interface Using Motor Imagery and SSVEP Based on Convolutional Neural Network
The key to electroencephalography (EEG)-based brain-computer interface (BCI) lies in neural decoding, and its accuracy can be improved by using hybrid BCI paradigms, that is, fusing multiple paradigms.
Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding
To this end, we propose a new method to solve the partial least square regression, named PLSR via optimization on bi-Grassmann manifold (PLSRbiGr).
Riemannian Manifold Optimization for Discriminant Subspace Learning
Linear discriminant analysis (LDA) is a widely used algorithm in machine learning to extract a low-dimensional representation of high-dimensional data, it features to find the orthogonal discriminant projection subspace by using the Fisher discriminant criterion.
HyperNTF: A Hypergraph Regularized Nonnegative Tensor Factorization for Dimensionality Reduction
However, most of tensor decomposition methods are the linear feature extraction techniques, which are unable to reveal the nonlinear structure within high-dimensional data.
Experimental Analysis of Legendre Decomposition in Machine Learning
In this technical report, we analyze Legendre decomposition for non-negative tensor in theory and application.
