Brain waves are commonly treated as if they were the sum of the outputs of a set of neural oscillators, each of which has a constant frequency and variable amplitude. This treatment is based on the assumption that brain dynamics is linear and time-invariant, which is clearly not the case. The advantage conveyed by this assumption is the ease with which linear analysis can be applied to brain waves using, e.g., Fast Fourier TransformFourier transform (FFT). The disadvantage is the inability of the linear analysis to capture and display the transient dynamicsTransientdynamics. IfStationary the signals are nonstationary, non-Gaussian, and significantly deviate from linear behavior, alternative approaches can be justified. In particular, the Hilbert TransformHilbert transform|( (HT) may be beneficial by giving high temporal resolution of signals undergoing phase and frequency modulation. Here we summarize the main signal processing approaches applied in EE/ECoG data evaluations.