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On Local Convergence of the Method of Alternating Projections

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TLDR
In this article, the authors proved local convergence of alternating projections between subanalytic sets under a mild regularity hypothesis on one of the sets, and showed that the speed of convergence is O(k √ √ σ(k − σ ) for some constant σ √ n, σ (n) for some σ σ = (0, √ N) √ (n − ρ) for any σ > 0.
Abstract
The method of alternating projections is a classical tool to solve feasibility problems. Here we prove local convergence of alternating projections between subanalytic sets $$A,B$$A,B under a mild regularity hypothesis on one of the sets. We show that the speed of convergence is $${\mathcal {O}}(k^{-\rho })$$O(k-?) for some $$\rho \in (0,\infty )$$??(0,?).

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Finding a low-rank basis in a matrix subspace

TL;DR: This work presents an algorithm based on a greedy process applicable to higher rank problems, which first estimates the minimum rank by applying soft singular value thresholding to a nuclear norm relaxation, and then computes a matrix with that rank using the method of alternating projections.
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Finding a low-rank basis in a matrix subspace

TL;DR: In this article, the authors present an algorithm based on a greedy process applicable to higher rank problems, which first estimates the minimum rank by applying soft singular value thresholding to a nuclear norm relaxation, and then computes a matrix with that rank using the method of alternating projections.
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Necessary conditions for linear convergence of iterated expansive, set-valued mappings with application to alternating projections

TL;DR: In this article, the authors present necessary conditions for monotonicity of fixed point iterations of mappings that violate the usual nonexpansive property of metric sub-regularity.
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Quantitative convergence analysis of iterated expansive, set-valued mappings

TL;DR: A framework for quantitative convergence analysis of Picard iterations of expansive set-valued fixed point mappings is developed, and a number of results showing local linear convergence of nonconvex cyclic projections for inconsistent (and consistent) feasibility problems are proved.
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Transversality in Variational Analysis

TL;DR: In this article, the Thom transversality theorem for semi-algebraic objects has been extended to variational analysis and optimization theory, and a set-valued version of the transversal theorem has been proved.
References
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Journal ArticleDOI

Phase retrieval algorithms: a comparison.

TL;DR: Iterative algorithms for phase retrieval from intensity data are compared to gradient search methods and it is shown that both the error-reduction algorithm for the problem of a single intensity measurement and the Gerchberg-Saxton algorithm forThe problem of two intensity measurements converge.
Journal Article

A practical algorithm for the determination of phase from image and diffraction plane pictures

R. W. Gerchberg
- 01 Jan 1972 - 
TL;DR: In this article, an algorithm is presented for the rapid solution of the phase of the complete wave function whose intensity in the diffraction and imaging planes of an imaging system are known.
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Splitting Algorithms for the Sum of Two Nonlinear Operators

TL;DR: This work studies two splitting algorithms for (stationary and evolution) problems involving the sum of two monotone operators with real-time requirements.
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Extending the methodology of X-ray crystallography to allow imaging of micrometre-sized non-crystalline specimens

TL;DR: Extending the methodology of X-ray crystallography to allow imaging of micrometre-sized non-crystalline specimens was proposed in this paper, where the authors extended the methodology to allow the imaging of micro-scale specimens.
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On Projection Algorithms for Solving Convex Feasibility Problems

TL;DR: A very broad and flexible framework is investigated which allows a systematic discussion of questions on behaviour in general Hilbert spaces and on the quality of convergence in convex feasibility problems.
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