Wavelet analysis is a mathematical tool used in signal processing and data analysis to decompose complex signals into simpler components called wavelets. These wavelets are scaled and translated versions of a "mother wavelet" function, which can be used to analyze the frequency content and structure of a signal at different scales. Wavelet analysis is commonly used in fields such as image processing, compression, time series analysis, and pattern recognition. It allows for both time-domain and frequency-domain analysis, providing a more localized and adaptive representation of signals compared to traditional Fourier analysis.