Outer reflected forward–backward splitting algorithm with inertial extrapolation step
Outer reflected forward–backward splitting algorithm with inertial extrapolation step
This paper studies an outer reflected forward–backward splitting algorithm with an inertial step to find a zero of the sum of three monotone operators composing the maximal monotone operator, Lipschitz monotone operator, and a cocoercive operator in real Hilbert spaces. One of the interesting features of the proposed method is that both the Lipschitz monotone operator and the cocoercive operator are computed explicitly each with one evaluation per iteration. We obtain weak and strong convergence results under some easy-to-verify assumptions. We also obtain a non-asymptotic (Formula presented.) convergence rate of our proposed algorithm in a non-ergodic sense. We finally give some numerical illustrations arising from compressed sensing and image processing and show that our proposed method is effective and competitive with other related methods in the literature.
Three operator splitting, inertial extrapolation step, non-asymptotic convergence rate, weak and strong convergence
3901-3924
Shehu, Yekini
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Jolaoso, Lateef O.
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Okeke, C.C.
051d0285-4fc7-4858-82cb-313d97c1b1a8
Xu, Renqi
fb90ad57-eb26-4750-90cc-ceef5cf90de7
Shehu, Yekini
df727925-5bf0-457a-87fa-f70de3bfd11a
Jolaoso, Lateef O.
102467df-eae0-4692-8668-7f73e8e02546
Okeke, C.C.
051d0285-4fc7-4858-82cb-313d97c1b1a8
Xu, Renqi
fb90ad57-eb26-4750-90cc-ceef5cf90de7
Shehu, Yekini, Jolaoso, Lateef O., Okeke, C.C. and Xu, Renqi
(2024)
Outer reflected forward–backward splitting algorithm with inertial extrapolation step.
Optimization, 74 (15), .
(doi:10.1080/02331934.2024.2391004).
Abstract
This paper studies an outer reflected forward–backward splitting algorithm with an inertial step to find a zero of the sum of three monotone operators composing the maximal monotone operator, Lipschitz monotone operator, and a cocoercive operator in real Hilbert spaces. One of the interesting features of the proposed method is that both the Lipschitz monotone operator and the cocoercive operator are computed explicitly each with one evaluation per iteration. We obtain weak and strong convergence results under some easy-to-verify assumptions. We also obtain a non-asymptotic (Formula presented.) convergence rate of our proposed algorithm in a non-ergodic sense. We finally give some numerical illustrations arising from compressed sensing and image processing and show that our proposed method is effective and competitive with other related methods in the literature.
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Inertial Shadow
- Accepted Manuscript
More information
Accepted/In Press date: 4 August 2024
e-pub ahead of print date: 14 August 2024
Keywords:
Three operator splitting, inertial extrapolation step, non-asymptotic convergence rate, weak and strong convergence
Identifiers
Local EPrints ID: 511375
URI: http://eprints.soton.ac.uk/id/eprint/511375
ISSN: 0233-1934
PURE UUID: 14721529-4829-4dc4-98d1-d5fac75683c2
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Date deposited: 13 May 2026 16:41
Last modified: 14 May 2026 02:02
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Contributors
Author:
Yekini Shehu
Author:
C.C. Okeke
Author:
Renqi Xu
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