Self-Rectifying Integrate-and-Fire Neuron and Collaborative Trim Training Framework for SNN-Based EEG Motor Imagery Classification

It can be seen that for spiking models, both the IF and SRIF method exhibit a clear trend of improved accuracy as T increases, which can be attributed to richer temporal feature extraction and reduced asynchronous errors with more time steps.

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