Research on the reconstruction of compressed EEG signals using deep learning is being explored. A hardware framework based on memristive crossbar arrays has been proposed for compressed sensing and neuromorphic processing. The approach involves methods such as deep unfolding network reconstruction and scalable sampling of transient signals.