Relaxing the Kaczmarz algorithm stabilizes noisy reconstructions from stationary sequences, removes corruption from noise in H^∞(D) or subspaces of H²(D), and stabilizes Fourier series expansions in L²(μ) for singular μ.
Positive Matrices in the Hardy Space with Prescribed Boundary Representations via the Kaczmarz Algorithm
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abstract
For a singular probability measure $\mu$ on the circle, we show the existence of positive matrices on the unit disc which admit a boundary representation on the unit circle with respect to $\mu$. These positive matrices are constructed in several different ways using the Kaczmarz algorithm. Some of these positive matrices correspond to the projection of the Szeg\H{o} kernel on the disc to certain subspaces of the Hardy space corresponding to the normalized Cauchy transform of $\mu$. Other positive matrices are obtained which correspond to subspaces of the Hardy space after a renormalization, and so are not projections of the Szeg\H{o} kernel. We show that these positive matrices are a generalization of a spectrum or Fourier frame for $\mu$, and the existence of such a positive matrix does not require $\mu$ to be spectral.
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math.FA 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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Stability of the Kaczmarz Reconstruction for Stationary Sequences
Relaxing the Kaczmarz algorithm stabilizes noisy reconstructions from stationary sequences, removes corruption from noise in H^∞(D) or subspaces of H²(D), and stabilizes Fourier series expansions in L²(μ) for singular μ.