Iteratively solving linear inverse problems under general convex constraints (Q995437): Difference between revisions

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scientific article; zbMATH DE number 5186384
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Latest revision as of 17:40, 11 July 2025

scientific article; zbMATH DE number 5186384
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Iteratively solving linear inverse problems under general convex constraints
scientific article; zbMATH DE number 5186384

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    Iteratively solving linear inverse problems under general convex constraints (English)
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    3 September 2007
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    Let \(T\) be a bounded operator from a Hilbert space \({\mathcal H}\) into itself, with \(\| T \|<1\), and \(C\) a closed convex subset of \({\mathcal H}\). For solving linear operator equations \(Tf=h\) the iterative process \(f_{n+1}=(\text{Id}-P_{\alpha C})(f_n+T^*g-T^* T f_n)\), \(\alpha>0\) is proposed. The cases of bounded and unbounded \((T^* T)^{-1}\) are considered.
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    linear inverse problems
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    Landweber iteration
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    Besov- and BV restoration
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    generalized shrinkage
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    Hilbert space
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    linear operator equations
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