Asymptotic complexity of Monte Carlo methods for solving linear systems

DOI10.1016/S0378-3758(99)00060-9zbMath0972.65025OpenAlexW1995228485MaRDI QIDQ1973275

John H. Halton, D. L. Danilov, Sergeĭ Mikhaĭlovich Ermakov

Publication date: 11 November 2001

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(99)00060-9

zbMATH Keywords

complexityMarkov processesstochastic algorithmmethod of successive iterationvon Neumann-Ulam Monte Carlo method

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Iterative numerical methods for linear systems (65F10) Complexity and performance of numerical algorithms (65Y20)

Related Items (7)

Biological applications and numerical solution based on Monte Carlo method for a two-dimensional parabolic inverse problem ⋮ Monte Carlo method via a numerical algorithm to solve a parabolic problem ⋮ Optimization of the quasi-Monte Carlo algorithm for solving systems of linear algebraic equations ⋮ Stochastic and quasistochastic computations ⋮ Monte Carlo simulation via a numerical algorithm for solving a nonlinear inverse problem ⋮ On construction of parallel algorithms in problems of computational mathematics ⋮ Stochastic version of the degenerate kernel method for solving large systems of linear equations with sparse matrix

Cites Work

• Monte-Carlo method with storage of intermediate results
• Asymptotic complexity of the collisions estimator for solving linear systems
• Random Numbers Generated by Linear Recurrence Modulo Two
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Asymptotic complexity of Monte Carlo methods for solving linear systems