Fourier analysis is not relevant to describe a signal when some of its properties change over time. This is the case, for example, for the chirp signal that we studied previously whose instantaneous frequency varies with time. This chapter reviews various methods for analyzing nonstationary signals. Multiplication of the signal by a sliding window leads to short-time Fourier analysis and spectrogram. In the Wigner–Ville distribution, the time reversed signal plays the role of a sliding window analyzer. The Continuous Wavelet Transform (CWT) principle is to explore the signal with a window whose width takes successively all possible values. We explain the theoretical basis of this method. Several wavelets are presented: Morlet, Mexican hat, and Shannon wavelets.