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These methods learn from data patterns rather than fixed equations.
Better performance in "real-world" environments with non-Gaussian noise. Digital Signal Processing with Kernel Methods
Transform input signals into a high-dimensional Hilbert space. These methods learn from data patterns rather than
Solve non-linear problems using linear geometry in that new space. Digital Signal Processing with Kernel Methods
Extracting non-linear features for signal compression.