Approximate Pruned and Truncated Haar Discrete Wavelet Transform VLSI Hardware for Energy-Efficient ECG Signal Processing

 The approximate computing paradigm emerged as a key alternative for trading off accuracy and energy efficiency. Error-tolerant applications, such as multimedia and signal processing, can process the information with lower-than-standard accuracy at the circuit level while still fulfilling a good and acceptable service quality at the application leve...

XOR-MUX Full Adder Approximate Pruned Haar Discrete Wavelet Transform VLSI ECG Signal Processing EEG Signal Processing

Self-Supervised Learning for Electroencephalography

 Decades of research have shown machine learning superiority in discovering highly nonlinear patterns embedded in electroencephalography (EEG) records compared with conventional statistical techniques. However, even the most advanced machine learning techniques require relatively large, labeled EEG repositories. EEG data collection and lab...

SSL methods EEG signals and brain function EEG pre-processing band-pass filtering SSL framework