Wang, Fenghui; Cui, Huanhuan - In: Journal of Global Optimization 54 (2012) 3, pp. 485-491
In this paper we consider the contraction-proximal point algorithm: <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$${x_{n+1}=\alpha_nu+\lambda_nx_n+\gamma_nJ_{\beta_n}x_n,}$$< /EquationSource> </InlineEquation> where <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$${J_{\beta_n}}$$</EquationSource> </InlineEquation> denotes the resolvent of a monotone operator A. Under the assumption that lim<Subscript> n </Subscript> α <Subscript> n </Subscript> = 0, ∑<Subscript> n </Subscript> α <Subscript> n </Subscript> = ∞, lim inf<Subscript> n </Subscript> β <Subscript> n...</subscript></subscript></subscript></subscript></subscript></subscript></equationsource></inlineequation></equationsource></inlineequation>