Asymptotic complexity of Monte Carlo methods for solving linear systems

Author:

Danilov D.L.,Ermakov S.M.,Halton J.H.

Publisher

Elsevier BV

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability

Reference14 articles.

1. Curtiss, J.H., 1956. A Theoretical comparision of the efficiencies of two classical methods and a Monte Carlo Method for computing one component of the solution of a set of linear algebraic equations. In: Meyer, H.A. (Ed.), Symp. on Monte Carlo Methods. Wiley, New York, pp. 191–233.

2. Danilov, D.L., Ermakov, S.M., 1995. On comparative complexity of the Monte Carlo method for solving linear systems. J. Comput. Math. Math. Phys. (in Russian), in press.

3. Ermakov, S.M., 1975. Die Monte Carlo Methode und verwandte Fragen. VEB Deutscher Verlag der Wissenschaften, Berlin.

4. Ermakov, S.M., Dovgal, V.V., 1991. On limit theorem for a Tausworthe random generator. Vestnik LGU (Ser. 1) 1, 105–106 (in Russian).

5. Ermakov, S.M., Melas, V.B., 1993. Mathematical Experiment with the Complex Stochastic Systems Models. Publishing House of St.- Petersburg University, St.-Petersburg.

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