<abstract xmlns="http://www.w3.org/1999/xhtml"><p>We present approximation theory of matrices based on its low ranking and stochastic computation. Finally, based on our introduced algorithm, we show the performance of these approximations to evaluate the desired results.</p></abstract>

We present approximation theory of matrices based on its low ranking and stochastic computation. Finally, based on our introduced algorithm, we show the performance of these approximations to evaluate the desired results.

A Way for Low Ranking Matrices and its Stochastic Computations Using Monte Carlo Method

Department of Statistics, The University of Guilan, Iran

Journal of Applied Mathematics, Statistics and Informatics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

We present approximation theory of matrices based on its low ranking and stochastic computation. Finally, based on our introduced algorithm, we show the...

A Way for Low Ranking Matrices and its Stochastic Computations Using Monte Carlo Method

Publié en ligne: 15 juil. 2014

Pages: 63 - 74

DOI: https://doi.org/10.2478/jamsi-2014-0006

Mots clés
Low rank, Randomized algorithm, Monte Carlo method, Singular value decomposition, Matrix multiplication

© 2014 Faculty of Natural Sciences, University of Saint Cyril and Metodius

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A Way for Low Ranking Matrices and its Stochastic Computations Using Monte Carlo Method

Publié en ligne: 15 juil. 2014

Pages: 63 - 74

DOI: https://doi.org/10.2478/jamsi-2014-0006

Mots clésLow rank, Randomized algorithm, Monte Carlo method, Singular value decomposition, Matrix multiplication

© 2014 Faculty of Natural Sciences, University of Saint Cyril and Metodius

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Low rank, Randomized algorithm, Monte Carlo method, Singular value decomposition, Matrix multiplication