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An efficient algorithm with double inertial steps for solving split common fixed point problems and an application to signal processing
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DOI：10.1007/s40314-024-03058-x.png)
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Abstract
En 中文
The split common fixed point problem is an optimization challenge that involves finding an element within one fixed point set such that when transformed by a bounded linear operator, it belongs to another fixed point set. This problem falls under the category of inverse problems in mathematics. We present a novel self-adaptive algorithm based on double inertial steps for solving the split common fixed point problem for demicontractive mappings. We also establish a weak convergence theorem for our method. Furthermore, we also present some numerical experiments illustrating the convergence behavior and the efficiency of our proposed algorithm.
Keywords:
Demicontractive operator
Double inertial steps
Self-adaptive algorithm
Signal processing
Split common fixed point problem
Journal
IF:
4.3
Papers:
354
Citations:
593
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