Discrete evolutionary transform for time-frequency analysis

We propose a new transformation for discrete signals with time-varying spectra. The kernel of this transformation provides the energy density of the signal in time-frequency. With this discrete evolutionary transform we obtain a representation for the signal as well as its time-frequency energy density. To obtain the kernel of the transformation we use either the Gabor or the Malvar discrete signal representations. Signal adaptive analysis can be done using modulated or chirped bases, and implemented with either masking or image segmentation on the time-frequency plane. Different examples illustrate the implementation of the discrete evolutionary transform.