We developed a signal reconstruction method, called SCSA, for pulse-shaped signal decomposition. After the decomposition, the reconstructioned signal will be composed of weighted sum of squared eigen-functions waveform of the Schrodinger operator. This method can also be used for signal denoising.
We developed a Feature extraction method, called SCSA, for pulse-shaped signal. It used the dimnesionality reduction principle based on Schrödinger operator.
We developed a Feature extraction method, called SCSA, for pulse-shaped signal. It used the dimnesionality reduction principle based on Schrödinger operator.
We developed a post-processing water suppression technique based on the squared eigenfunctions of the Schrodinger operator.
New Feature extraction method based on the Quantization-based Semi-Classical Signal Analysis designed explicitly for epileptic spikes using Magnetoencephalography (MEG) signals.
Investigate the potentials of the semi-classical signal algorithm (SCSA) for biosignal estimation.