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[11] proposes a projection algorithm for solving the multi-valued variational inequality with a pseudomonotone mapping.
Recently, [15] proposes a projection algorithm for generalized variational inequality with pseudomonotone mapping.
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We propose a new projection algorithm for generalized variational inequality with multivalued mapping.
In Section 3, we propose a hybrid CQ projection algorithm for the split feasibility problem and show its convergence.
In this paper, motivated by the selfadaptive method and hybrid projection method for solving variational inequality problem, based on the CQ algorithm for the SFP, we propose a hybrid CQ projection algorithm for the split feasibility problem, which uses different variable stepsizes in two projection steps.
A novel model for freeform surface parameterisation is introduced; this new model proposes the use of a projection algorithm before the actual calculation of the parameters.
Using the statistical property of the system noise, a projection algorithm is proposed for parameter estimation.
We also proposed a projection model for Hadoop K-means workload.
In what follows, we propose a projection gradient optimization algorithm to solve the resulting minimization problems.
In this paper, we introduce a different projection algorithm for generalized variational inequality.
Yet others have proposed a projection on regularly spaced vectors for HS pattern recognition [28].
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