In this paper, we propose a self adaptive spectral conjugate gradient-based projection method for systems of nonlinear monotone equations. Based on its modest memory requirement and its efficiency, the method is suitable for solving large-scale equations. We show that the method satisfies the descent condition FT k dk ≤ −cFk2, c > 0, and also prove its global convergence. The method is compared to other existing methods on a set of benchmark test problems and results show that the method is very efficient and therefore promising.
Koorapetse, M., & Kaelo, P. (2020). Self adaptive spectral conjugate gradient method for solving nonlinear monotone equations. Journal of the Egyptian Mathematical Society, 28(1), 1-21. doi: 10.1186/s42787-019-0066-1
MLA
M. Koorapetse; P. Kaelo. "Self adaptive spectral conjugate gradient method for solving nonlinear monotone equations", Journal of the Egyptian Mathematical Society, 28, 1, 2020, 1-21. doi: 10.1186/s42787-019-0066-1
HARVARD
Koorapetse, M., Kaelo, P. (2020). 'Self adaptive spectral conjugate gradient method for solving nonlinear monotone equations', Journal of the Egyptian Mathematical Society, 28(1), pp. 1-21. doi: 10.1186/s42787-019-0066-1
VANCOUVER
Koorapetse, M., Kaelo, P. Self adaptive spectral conjugate gradient method for solving nonlinear monotone equations. Journal of the Egyptian Mathematical Society, 2020; 28(1): 1-21. doi: 10.1186/s42787-019-0066-1
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