A Robust and Accurate Quasi-Monte Carlo Algorithm for Estimating Eigenvalue of Homogeneous Integral Equations | Zendy

Farshid Mehrdoust | Zendy; Behrouz Fathi Vajargah | Zendy; E. Radmoghaddam | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A Robust and Accurate Quasi-Monte Carlo Algorithm for Estimating Eigenvalue of Homogeneous Integral Equations

Author(s) -

Farshid Mehrdoust,

Behrouz Fathi Vajargah,

E. Radmoghaddam

Publication year - 2013

Publication title -

isrn computational mathematics

Language(s) - English

Resource type - Journals

ISSN - 2090-7842

DOI - 10.1155/2013/891029

Subject(s) - monte carlo method , eigenvalues and eigenvectors , variance reduction , algorithm , mathematics , homogeneous , sequence (biology) , hybrid monte carlo , quasi monte carlo method , variance (accounting) , mathematical optimization , computer science , markov chain monte carlo , statistics , physics , combinatorics , accounting , quantum mechanics , biology , business , genetics

We present an efficient numerical algorithm for computing the eigenvalue of the linear homogeneous integral equations. The proposed algorithm is based on antithetic Monte Carlo algorithm and a low-discrepancy sequence, namely, Faure sequence. To reduce the computational time we reduce the variance by using the antithetic variance reduction procedure. Numerical results show that our scheme is robust and accurate.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research