Tian Ming, Zhang Hui-Fang
College of Science, Civil Aviation University of China, Tianjin, 300300 China.
Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China, Tianjin, 300300 China.
J Inequal Appl. 2017;2017(1):207. doi: 10.1186/s13660-017-1480-2. Epub 2017 Sep 5.
The split feasibility problem (SFP) is finding a point [Formula: see text] such that [Formula: see text], where and are nonempty closed convex subsets of Hilbert spaces [Formula: see text] and [Formula: see text], and [Formula: see text] is a bounded linear operator. Byrne's CQ algorithm is an effective algorithm to solve the SFP, but it needs to compute [Formula: see text], and sometimes [Formula: see text] is difficult to work out. López introduced a choice of stepsize [Formula: see text], [Formula: see text], [Formula: see text]. However, he only obtained weak convergence theorems. In order to overcome the drawbacks, in this paper, we first provide a regularized CQ algorithm without computing [Formula: see text] to find the minimum-norm solution of the SFP and then obtain a strong convergence theorem.
分裂可行性问题(SFP)是要找到一个点[公式:见正文],使得[公式:见正文],其中[公式:见正文]和[公式:见正文]是希尔伯特空间[公式:见正文]和[公式:见正文]中的非空闭凸子集,且[公式:见正文]是一个有界线性算子。伯恩的CQ算法是解决SFP的一种有效算法,但它需要计算[公式:见正文],而有时[公式:见正文]很难算出。洛佩斯引入了步长的一种选择[公式:见正文],[公式:见正文],[公式:见正文]。然而,他只得到了弱收敛定理。为了克服这些缺点,在本文中,我们首先提供一种无需计算[公式:见正文]的正则化CQ算法来找到SFP的最小范数解,然后得到一个强收敛定理。