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An Extension of the Gradient Algorithm

In: Convex Optimization with Computational Errors

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  • Alexander Zaslavski

    (Israel Institute of Technology)

Abstract

In this chapter we analyze the convergence of a gradient type algorithm, under the presence of computational errors, which was introduced by Beck and Teboulle (SIAM J Imaging Sci 2:183–202, 2009) for solving linear inverse problems arising in signal/image processing.

Suggested Citation

  • Alexander Zaslavski, 2020. "An Extension of the Gradient Algorithm," Springer Optimization and Its Applications, in: Convex Optimization with Computational Errors, chapter 0, pages 151-171, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-37822-6_5
    DOI: 10.1007/978-3-030-37822-6_5
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