Uncertainty principles and signal recovery
SIAM Journal on Applied Mathematics
The product of affine orthogonal projections
Journal of Approximation Theory
Ten lectures on wavelets
Nazarov's uncertainty principles in higher dimension
Journal of Approximation Theory
The rate of convergence for the cyclic projections algorithm III: Regularity of convex sets
Journal of Approximation Theory
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A common problem in applied mathematics is that of finding a function in a Hilbert space with prescribed best approximations from a finite number of closed vector subspaces. In the present paper we study the question of the existence of solutions to such problems. A finite family of subspaces is said to satisfy the Inverse Best Approximation Property (IBAP) if there exists a point that admits any selection of points from these subspaces as best approximations. We provide various characterizations of the IBAP in terms of the geometry of the subspaces. Connections between the IBAP and the linear convergence rate of the periodic projection algorithm for solving the underlying affine feasibility problem are also established. The results are applied to investigate problems in harmonic analysis, integral equations, signal theory, and wavelet frames.