Traditional DSP relies on and stationarity . Kernel methods break these limits by using the "Kernel Trick" :
Providing probabilistic bounds for signal estimation. 🚀 Why It Matters
These methods learn from data patterns rather than fixed equations.
Better performance in "real-world" environments with non-Gaussian noise.