4 papers
Convergence Rates for Variational Inequality Projection Neural Networks with a State-Dependent Metric
Mohammed Alshahrani
We study continuous-time projection neural networks for variational inequalities on closed convex sets. A positive definite matrix that depends on the state preconditions the opera…
Projection and contraction methods with double inertial steps for variational inclusion problems on Hilbert spaces
Moin Uddin, Mohammed Alshahrani, Qamrul Hasan Ansari
In this paper, we propose three projection--contraction algorithms for solving variational inclusion problems in the setting of Hilbert spaces, each incorporating a double inertial…
State-Dependent Metric Projection Neural Network for Variational Inequalities
Mohammed Alshahrani
Projection-based dynamical systems and projection neural networks offer a continuous-time approach to solving variational inequalities by driving the state toward its projection on…
Two Generalized Derivative-free Methods to Solve Large Scale Nonlinear Equations with Convex Constraints
Kabenge Hamiss, Mohammed M. Alshahrani, Mujahid N. Syed
In this work, we propose two derivative-free methods to address the problem of large-scale nonlinear equations with convex constraints. These algorithms satisfy the sufficient desc…