👉 Depth math, also known as multiscale analysis or wavelet analysis, is a mathematical framework that studies functions and their properties across multiple scales or resolutions. It involves decomposing signals or data into different frequency components, allowing for the analysis of both global trends and local details. This is achieved through tools like wavelets, which are functions that can be scaled and shifted to capture variations at various levels of detail. By examining data in this multi-resolution context, depth math enables the extraction of features that might be obscured when looking at a single scale, making it particularly useful in fields like image processing, signal analysis, and financial modeling where understanding both broad patterns and fine-grained details is crucial.
