New inertial relaxed CQ regularization methods for the multiple-sets splitting feasibility problem

Wenting Chen; Meixia Li

doi:10.1117/12.2639062

15 July 2022 New inertial relaxed CQ regularization methods for the multiple-sets splitting feasibility problem

Wenting Chen, Meixia Li

Proceedings Volume 12258, International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022); 1225802 (2022) https://doi.org/10.1117/12.2639062
Event: International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022), 2022, Qingdao, China

Abstract

The multiple-sets splitting feasibility problem (MSSFP) is the extension of splitting feasibility problem. This problem has been widely used in visual neural network and fuzzy image processing system. In this article, we offer the regularization methods of the inertial relaxed CQ algorithm, where the choice of parameters is not related to the operator norm. Under certain conditions, the weak convergence of the sequences is proved. In addition, the convergence of the algorithm is verified by numerical experiments.

Citation Download Citation

Wenting Chen and Meixia Li "New inertial relaxed CQ regularization methods for the multiple-sets splitting feasibility problem", Proc. SPIE 12258, International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022), 1225802 (15 July 2022); https://doi.org/10.1117/12.2639062

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