This chapter provides a foundational introduction to wavelet analysis, beginning with a review of classical time-frequency representations. The Fourier transform is discussed as a fundamental tool for analyzing signals in the frequency domain. The limitations of Fourier transform in handling nonstationary signals lead to the introduction of the short-time Fourier transform (STFT) which incorporates a fixed window function for localized spectral analysis. However, the trade-off between time and frequency resolution in STFT motivates the need for the continuous wavelet transform (CWT), which employs scalable basis functions for adaptive time-frequency resolution. The chapter then introduces the discrete wavelet transform (DWT), which enables efficient multiresolution analysis through dyadic scaling and translation.