The wavelet transform modulus maxima (WTMM) is a method for detecting the fractal dimension of a signal.
More than this, the WTMM is capable of partitioning the time and scale domain of a signal into fractal dimension regions, and the method is sometimes referred to as a "mathematical microscope" due to its ability to inspect the multi-scale dimensional characteristics of a signal and possibly inform about the sources of these characteristics.
(Compare this to a Taylor series, where in practice only a limited number of low-order terms are used to approximate a continuous function.)
Choice of wavelet may depend on characteristics of the signal being investigated.
Successive derivative wavelets remove the contribution of lower order terms in the signal, allowing the maximum
Thus, this method identifies the singularity spectrum by convolving the signal with a wavelet at different scales and time offsets.
The WTMM is then capable of producing[vague] a "skeleton" that partitions the scale and time space by fractal dimension.
The WTMM was developed out of the larger field of continuous wavelet transforms, which arose in the 1980s, and its contemporary fractal dimension methods.
WTMM was originally developed by Mallat and Hwang in 1992 and used for image processing [1].
Bacry, Muzy, and Arneodo were early users of this methodology.