Reproducing kernel structure and sampling on time-warped spaces with application to warped wavelets

Time-warped signal spaces have received attention in the literature. Among the topics of particular interest are sampling of time-warped signals and signal analysis using warped analysis functions, including wavelets. This correspondence introduces a reproducing kernel (RK) structure for time-warped signal spaces that unifies multiple perspectives on sampling in such spaces.