Stochastic electroencephalogram (EEG) signals are known to be nonstationary and often multicomponential. Detecting and extracting their components may help clinicians to localize brain neurological dysfunctionalities for patients with motor control disorders due to the fact that movement-related cortical activities are reflected in spectral EEG changes. A new algorithm for EEG signal components detection from its […]
Laboratory for Information Processing and Pattern Recognition
Improved LPA-ICI-Based Estimators Embedded in a Signal Denoising Virtual Instrument
Adaptive filters embedded in a user-friendly virtual instrument (VI) for signal denoising are proposed in the paper. The filters are based on the local polynomial approximation (LPA) and equipped with the improved intersection of confidence intervals (ICI) rule, known as the relative intersection of confidence intervals (RICI) rule, in order to achieve adaptivity to high […]
