Posted by **Bayron** at Sept. 14, 2015

English | 2009 | ISBN: 0691140626 | 776 pages | PDF | 38 MB

Posted by **interes** at May 2, 2015

English | 2009 | ISBN: 0691140626 | 776 pages | PDF | 6,3 MB

Posted by **libr** at Jan. 6, 2014

English | 2009 | ISBN: 0691140626 | 776 pages | PDF | 6,3 MB

Probability, Markov Chains, Queues, and Simulation provides a modern and authoritative treatment of the mathematical processes that underlie performance modeling. The detailed explanations of mathematical derivations and numerous illustrative examples make this textbook readily accessible to graduate and advanced undergraduate students taking courses in which stochastic processes play a fundamental role.

Posted by **ksveta6** at March 30, 2016

2013 | ISBN: 9814451509 | English | 354 pages | EPUB | 4 MB

Posted by **bookwyrm** at Dec. 25, 2014

2013 | 287 Pages | ISBN: 3642331300 | PDF | 3 MB

Posted by **tukotikko** at Oct. 10, 2014

2013 | 287 Pages | ISBN: 3642331300 | PDF | 3 MB

Posted by **interes** at Oct. 1, 2014

English | 2013 | ISBN: 9814451509 | 350 pages | PDF | 3,2 MB

This book provides an undergraduate introduction to discrete and continuous-time Markov chains and their applications. A large focus is placed on the first step analysis technique and its applications to average hitting times and ruin probabilities.

Posted by **JohnZulzman** at Sept. 23, 2014

Wiley-Interscience; 2 edition | ISBN: 0471565253 | 896 pages | PDF | April 14, 2006 | English | 44 Mb

Posted by **interes** at June 23, 2014

English | 2013 | ISBN: 1848214936 | ISBN-13: 9781848214934 | 416 pages | PDF | 2,7 MB

Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communication networks and manufacturing systems.

Posted by **interes** at May 31, 2014

English | 2014 | ISBN: 1118517075 | ISBN-13: 9781118517079 | 258 pages | PDF | 4,6 MB

Markov Chains: Analytic and Monte Carlo Computations introduces the main notions related to Markov chains and provides explanations on how to characterize, simulate, and recognize them. Starting with basic notions, this book leads progressively to advanced and recent topics in the field, allowing the reader to master the main aspects of the classical theory.