Multiclass support matrix machines by maximizing the inter-class margin for single trial EEG classification

Keyphrases

• Electroencephalography 100%
• Multi-class 100%
• Electroencephalogram Classification 100%
• Support Matrix Machine 100%
• Regularization Term 66%
• Copyright 33%
• Mental Activity 33%
• Statistical Test 33%
• Accurate Classification 33%
• Multiple Predictors 33%
• Experiment Results 33%
• Classification Performance 33%
• Noisy Data 33%
• Brain-computer Interface 33%
• Generalization Ability 33%
• Hinge Loss 33%
• Elastic Net Penalty 33%
• Frobenius Norm 33%
• Structured Sparsity 33%
• Motor Imagery 33%
• Sparsity Pattern 33%
• Nuclear Norm 33%
• C-matrix 33%

Computer Science

• Regularization Term 100%
• Objective Function 50%
• Sparsity 50%
• Computer Interface 50%
• Classification Performance 50%
• Nuclear Norm 50%
• Sparsity Pattern 50%

Engineering

• Support Matrix 100%
• Regularization 66%
• Objective Function 33%
• Brain-Computer Interface 33%
• Sparsity 33%
• Noisy Data 33%
• Classification Performance 33%
• Motor Imagery 33%
• Sparsity Pattern 33%