Random Tight Frames

Abstract

We introduce probabilistic frames to study finite frames whose elements are chosen at random. While finite tight frames generalize orthonormal bases by allowing redundancy, independent, uniformly distributed points on the sphere approximately form a finite unit norm tight frame (FUNTF). In the present paper, we develop probabilistic versions of tight frames and FUNTFs to significantly weaken the requirements on the random choice of points to obtain an approximate finite tight frame. Namely, points can be chosen from any probabilistic tight frame, they do not have to be identically distributed, nor have unit norm. We also observe that classes of random matrices used in compressed sensing are induced by probabilistic tight frames.

References in corpus (1)

• Frame theory in directional statistics

Cited by in corpus (8)

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• Preconditioning filter bank decompositions using structured normalized tight frames
• Approximately Dual and Pseudo-Dual Probabilistic Frames