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Conjugate gradient-based projection methods are widely used for solving large-scale nonlinear monotone equations. This is due to their simplicity and that they are derivative-free. In this paper, we propose another conjugate gradient-based projection method for large-scale nonlinear monotone equations. We show that the method satisfies the descent condition independent of line searches and that the method is globally convergent. Numerical results show that the method is both efficient and effective.

A derivative-free conjugate gradient projection method based on the memoryless BFGS update