Abstract
The CQ algorithm is widely used in the scientific field and has a significant impact on phase retrieval, medical image reconstruction, signal processing, etc. Moudafi proposed an alternating CQ algorithm to solve the split equality problem, but he only obtained the result of weak convergence. The work of this paper is to improve his algorithm so that the generated iterative sequence can converge strongly.
Highlights
Let C ⊆ H1, Q ⊆ H2 be two nonempty closed convex subsets, H1 and H2 are realHilbert spaces
It is used to model the inverse problems of phase retrieval and medical image reconstruction in finite-dimensional Hilbert spaces. It has a significant impact on signal processing, image reconstruction and radiation therapy, see [2,3,4]
We propose an improved alternating CQ algorithm to solve the split equality problem (SEP)
Summary
It is used to model the inverse problems of phase retrieval and medical image reconstruction in finite-dimensional Hilbert spaces. It has a significant impact on signal processing, image reconstruction and radiation therapy, see [2,3,4]. The following CQ algorithm proposed by Byrne [4] is an important method to solve the SFP un+1 = PC (un + ρA∗ ( PQ − I ) Aun ), n ≥ 0. We propose an improved alternating CQ algorithm to solve the SEP This improved method changes the iterative sequence from weak to strong convergence.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
