Using for EEG/ECG pulse recognition. Differentiating noise from complex biological signals. Denoising & Regression
Better performance in "real-world" environments with non-Gaussian noise. Digital Signal Processing with Kernel Methods
Traditional DSP relies on and stationarity . Kernel methods break these limits by using the "Kernel Trick" : Using for EEG/ECG pulse recognition
Solve non-linear problems using linear geometry in that new space. Digital Signal Processing with Kernel Methods
Using for EEG/ECG pulse recognition. Differentiating noise from complex biological signals. Denoising & Regression
Better performance in "real-world" environments with non-Gaussian noise.
Traditional DSP relies on and stationarity . Kernel methods break these limits by using the "Kernel Trick" :
Solve non-linear problems using linear geometry in that new space.