This paper develops two implementations of halpern-type proximal algorithms(HPA1 and HPA2) solving nonsmooth *** prove their convergence to the solutions of the problems under the new *** this idea to the Basis Pursui...
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ISBN:
(纸本)9781509001668
This paper develops two implementations of halpern-type proximal algorithms(HPA1 and HPA2) solving nonsmooth *** prove their convergence to the solutions of the problems under the new *** this idea to the Basis Pursuit model in image/signal processing,a new halpern-type proximal algorithm(HPA) for the model is *** show that the halpern-type proximal algorithm has better descent property than the usual proximal algorithm(PA) for the Basis Pursuit model.
The main result of this paper is to prove the strong convergence of the sequence generated by the proximal point algorithm of halperntype to a zero of a maximal monotone operator under the suitable assumptions on the...
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The main result of this paper is to prove the strong convergence of the sequence generated by the proximal point algorithm of halperntype to a zero of a maximal monotone operator under the suitable assumptions on the parameters and error. The results extend some of the previous results or give some different conditions for convergence of the sequence. It is also indicated that when the maximal monotone operator is the subdifferential of a convex, proper, and lower semicontinuous function, the results extend all previous results in the literature. We also prove the boundedness of the sequence generated by the algorithm with a weak coercivity condition defined in the paper and without any additional assumptions on the parameters.
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