DocumentCode
1894356
Title
An optimal importance sampling method for a transient Markov system
Author
Qi, Hongui ; Wei, Michael ; Lei Wei
Author_Institution
Sch. of Electr., Comput. & Telecommun. Eng., Wollongong Univ., NSW, Australia
Volume
2
fYear
2001
fDate
25-29 Nov. 2001
Firstpage
1152
Abstract
In this paper an optimal importance sampling (IS) method is derived for a transient Markov system. Several propositions are presented. It is shown that the optimal IS method is unique, and it must converge to the standard Monte Carlo (MC) simulation method when the sample path length approaches infinity. Therefore, it is not the size of the state space of the Markov system, but the sample path length, that limits the efficiency of the IS method. Numerical results are presented to support the argument.
Keywords
Markov processes; Monte Carlo methods; importance sampling; optimisation; Monte Carlo simulation; optimal importance sampling; sample path length; transient Markov system; Analytical models; Australia; Computational modeling; Computer networks; Error probability; H infinity control; Monte Carlo methods; Performance analysis; State-space methods; Telecommunication computing;
fLanguage
English
Publisher
ieee
Conference_Titel
Global Telecommunications Conference, 2001. GLOBECOM '01. IEEE
Conference_Location
San Antonio, TX, USA
Print_ISBN
0-7803-7206-9
Type
conf
DOI
10.1109/GLOCOM.2001.965662
Filename
965662
Link To Document