AbstractRecently, Lu and Hurvich [Y. Lu, C. Hurvich, On the complexity of the preconditioned conjugate gradient algorithm for solving toeplitz systems with a Fisher–Hartwig singularity, SIAM J. Matrix Anal. Appl. 27 (2005) 638–653] used the preconditioned conjugate gradient method with the optimal circulant preconditioner proposed in Chan [T. Chan, An optimal circulant preconditioner for Toeplitz systems, SIAM J. Sci. Statist. Comput. 9 (1988) 766–771] for solving the Toeplitz system Tn(f)x=b where the generating function f is given byf(ω)=|1-e-iω|-2dh(ω)with d∈-12,12⧹{0}. The function h(ω) is positive continuous on [-π,π] and differentiable on [-π,π]⧹{0}. In this paper, we will use the superoptimal circulant preconditioner proposed by Tyrt...
AbstractWe study a non-linear minimization problem on H01(Ω)⊂Lq with q=2nn−2: inf‖u‖Lq=1∫Ω(1+|x|β|u|...
AbstractIn this paper, we study the convergence of Gauss–Newton's like method for nonlinear least sq...
We give here a proof of the convergence of the Stochastic Gradient Descent (SGD) in a self-contained...
AbstractFor any given n-by-n matrix An, T. Chan’s circulant preconditioner cF(An) proposed by T. Cha...
We derive novel explicit formulas for the inverses of truncated block Toeplitz matrices that corresp...
International audienceThe CSA-ES is an Evolution Strategy with Cumulative Step size Adaptation, wher...
AbstractIn this short note, it is proved that given any positive definite Hermitian matrix, the eige...
We provide an improvment of the maximum principle of Pon-tryagin of the optimal control problems, fo...
AbstractThe numerical-analytic method is applied to a class of nonlinear differential-algebraic syst...
We study the role of preconditioning strategies recently developed for coercive problems in connect...
We study the role of preconditioning strategies recently developed for coercive problems in connect...
We study the role of preconditioning strategies recently developed for coercive problems in connect...
Z. Kovarik proposed in 1970 a method for approximate orthogonalization of a finite set of linearly i...
AbstractLi et al. [Y.T. Li, C. Li, S. Wu, Improvements of preconditioned AOR iterative methods for L...
To solve iteratively linear system $Au=b$ with large sparse strongly non-symmetric matrix $A$ we pro...
AbstractWe study a non-linear minimization problem on H01(Ω)⊂Lq with q=2nn−2: inf‖u‖Lq=1∫Ω(1+|x|β|u|...
AbstractIn this paper, we study the convergence of Gauss–Newton's like method for nonlinear least sq...
We give here a proof of the convergence of the Stochastic Gradient Descent (SGD) in a self-contained...
AbstractFor any given n-by-n matrix An, T. Chan’s circulant preconditioner cF(An) proposed by T. Cha...
We derive novel explicit formulas for the inverses of truncated block Toeplitz matrices that corresp...
International audienceThe CSA-ES is an Evolution Strategy with Cumulative Step size Adaptation, wher...
AbstractIn this short note, it is proved that given any positive definite Hermitian matrix, the eige...
We provide an improvment of the maximum principle of Pon-tryagin of the optimal control problems, fo...
AbstractThe numerical-analytic method is applied to a class of nonlinear differential-algebraic syst...
We study the role of preconditioning strategies recently developed for coercive problems in connect...
We study the role of preconditioning strategies recently developed for coercive problems in connect...
We study the role of preconditioning strategies recently developed for coercive problems in connect...
Z. Kovarik proposed in 1970 a method for approximate orthogonalization of a finite set of linearly i...
AbstractLi et al. [Y.T. Li, C. Li, S. Wu, Improvements of preconditioned AOR iterative methods for L...
To solve iteratively linear system $Au=b$ with large sparse strongly non-symmetric matrix $A$ we pro...
AbstractWe study a non-linear minimization problem on H01(Ω)⊂Lq with q=2nn−2: inf‖u‖Lq=1∫Ω(1+|x|β|u|...
AbstractIn this paper, we study the convergence of Gauss–Newton's like method for nonlinear least sq...
We give here a proof of the convergence of the Stochastic Gradient Descent (SGD) in a self-contained...