Random average sampling and reconstruction in a reproducing kernel space
Yaxu Li,
Jun Xian
Abstract:Suppose that signals of interest reside in a reproducing kernel space defined on a metric measure space. We consider the scenario that the sampling positions are distributed on a bounded domain
of a metric measure space, and the sampling data are local averages of the original signals in a reproducing kernel space. For signals concentrated on
in that reproducing kernel space, we study the stability of this sampling procedure by establishing a weighted sampling inequality of bi‐Lipschitz type. This type of … Show more
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