We consider scale-covariant quadratic time-frequency representations (QTFR's) specifically suited for the analysis of signals passing through dispersive systems. These QTFR's satisfy a scale covariance property that is equal to the scale covariance property satisfied by the continuous wavelet transform and a covariance property with respect to generalized time shifts. We derive an existence/representation theorem that shows the exceptional role of time shifts corresponding to group delay functions that are proportional to powers of frequency. This motivates the definition of the power classes (PC's) of QTFR's. The PC's contain the afflne QTFR class as a special case, and thus, they extend the afflne class. In particular, the PC's extend the afflne scalogram (squared magnitude of the continuous wavelet transform) to a new QTFR-the powergram (squared magnitude of a warped wavelet transform). We show that the PC's can be defined axiomatically by the two covariance properties they satisfy, or they can be obtained from the afflne class through a warping transformation. We discuss signal transformations related to the PC's, the description of the PC's by kernel functions, desirable properties and kernel constraints, specific PC members, and three important PC subclasses. Finally, we present simulation results that demonstrate the potential advantage of PC QTFR's.
|Original language||English (US)|
|Number of pages||1|
|Journal||IEEE Transactions on Signal Processing|
|State||Published - Dec 1 1997|
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering