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Inverse Lithography Technology (ILT) Under Chip Manufacture Context. [PDF]
Micromachines (Basel)Meng X, Chen C, Ni J.
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The impact of CNN MHAM-enhanced WRF and BPNN models for user behavior prediction. [PDF]
Sci RepZheng K, Liang Z.
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Analysis of thermal conductivity of aluminum alloys by compositions and tempering process using machine learning. [PDF]
Sci RepShawon AR, Ghosh R, Islam MA.
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A Nonlinear Conjugate Gradient Methods Based on a Modified Secant Condition
, 2013 Basim A. Hassan
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Convergence Properties of Nonlinear Conjugate Gradient Methods
SIAM Journal on Optimization, 2000The authors study a class of conjugate gradient-type methods \(x_{k+1}=x_k+\lambda_k d_k, d_k=-f''(x_k)+\beta_k d_{k-1}\) for the unconstrained minimization problem \(\min_{x \in R^n} f(x)\). Let \(f(x)\) be bounded below on \(L=\{x \in R^n: f(x) \leq f(x_1) \}\) and \(f''(x)\) be Lipschitz continuous on \(L\) where \(L\) may be unbounded. Suppose that
Dai, Yuhong +5 more
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Nonlinear Conjugate Gradient Methods for Vector Optimization
SIAM Journal on Optimization, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lucambio Pérez, L. R., Prudente, L. F.
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A new nonlinear conjugate gradient method
AIP Conference Proceedings, 2015Conjugate gradient (CG) methods are essential for solving large-scale unconstrained optimization problems. Many of studies and modifications have been practiced to improve this method. In this paper, a new class of conjugate gradient coefficients (βk) with a new parameter m = ‖gk‖‖dk−1‖ that possess global convergence properties is presented.
Awad Abdelrahman +4 more
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Two Adaptive Dai–Liao Nonlinear Conjugate Gradient Methods
Iranian Journal of Science and Technology, Transactions A: Science, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Babaie-Kafaki, Saman, Ghanbari, Reza
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Conjugate gradient method for adaptive nonlinear filtering
Proceedings of 1994 37th Midwest Symposium on Circuits and Systems, 2002The application of the Conjugate Gradient (CG) method for the identification of a new class of non-linear discrete time systems, called "Generalized Bilinear System" is investigated. An algorithm based on the CG method is developed for adaptive generalized bilinear filtering with output error method.
S. Rajan +3 more
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