Neurobiology of Aging: Contents

By Michele Benzi, Gene H. Golub, Jörg Liesen. Acta Numerica, 2005

734 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computational Theory and Mathematics, Numerical Analysis

View Paper: https://www.semanticscholar.org/paper/3f7f085c352edef8cd8aa30a35869692e268ae6e

Citations in the corpus

• Image upsampling via imposed edge statistics (2007, neutral): “The solver used in our implementation is equivalent to a basic Conjugate Gradient -based Null Space method as described in [Press et al. 1993] and [Benzi et al. 2005].”
• A Robust Algorithm for Power System State Estimation With Equality Constraints (2010, neutral): “However, other permutations might exist such that the permuted matrix cannot be factorized [ 24 ].”
• BOUNDARY CONDITIONS IN APPROXIMATE COMMUTATOR PRECONDITIONERS FOR THE NAVIER-STOKES EQUATIONS ∗ (2009, neutral): “A survey of solver algorithms and issues associated with saddle point systems appears in [1].”
• On semi-convergence of parameterized Uzawa methods for singular saddle point problems☆ (2009, neutral): “More related works can be found in [4,6,9,3].”
• Energy-momentum conserving integration of multibody dynamics (2007, neutral): “[4]).”
• A note on the Drazin inverse of an anti-triangular matrix (2009, neutral): “IfA arises fromaconstrainedvariational or optimization 44 problem [1] (KKT linear systems), then it is usual that B = C .”
• Low-rank solvers for unsteady Stokes–Brinkman optimal control problem with random data (2016, neutral): “[7].”
• Reduced basis approximation and a posteriori error bounds for 4D-Var data assimilation (2018, neutral): “(8d) where the nal condition of the adjoint is given by p;K+1 = 0.Concerning the existence and uniqueness of the 4D-Var problem specically and of saddle point problems in general we refer to [4] and [3]. 3.1.1 Algebraic Formulation The 4D-Var problem is usually stated using an algebraic formulation ”
• Split Bregman Methods and Frame Based Image Restoration (2009, neutral): “Similar to the discussion for (4.6), the cost of algorithm (4.8) at each step is also O ( n log n ).”