wavelet basis functions

Wavelet basis functions are mathematical tools used to analyze signals or data by breaking them down into different frequency components. Unlike traditional methods that focus on specific frequencies, wavelets can capture both frequency and location in a signal. This makes them particularly useful for detecting patterns or changes over time, such as in audio, images, or other complex data. Wavelets resemble tiny waves that can stretch and compress, allowing them to adapt to various features in the data, thereby offering a flexible way to understand and represent information across different scales.