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[null,"1.","Record Nr.",null,"UNINA9910956108003321"]
[null,null,"Autore",null,"Bremaud Pierre"]
[null,null,"Titolo",null,"Markov Chains : Gibbs Fields, Monte Carlo Simulation, and Queues / / by Pierre Bremaud"]
[null,null,"Pubbl/distr/stampa",null,"New York, NY : , : Springer New York : , : Imprint : Springer, , 1999"]
[null,null,"ISBN",null,"1-4757-3124-8"]
[null,null,"Edizione",null,"[1st ed. 1999.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVIII, 445 p. 3 illus.)"]
[null,null,"Collana",null,"Texts in Applied Mathematics, , 2196-9949 ; ; 31"]
[null,null,"Disciplina",null,"519.2"]
[{"$nulls":4},"519.233"]
[null,null,"Soggetti",null,"Probabilities"]
[{"$nulls":4},"Operations research"]
[{"$nulls":4},"Electrical engineering"]
[{"$nulls":4},"Probability Theory"]
[{"$nulls":4},"Operations Research and Decision Theory"]
[{"$nulls":4},"Electrical and Electronic Engineering"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","\"With 64 Illustrations.\""]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and indexes."]
[null,null,"Nota di contenuto",null,"1 Probability Review -- 2 Discrete-Time Markov Models -- 3 Recurrence and Ergodicity -- 4 Long Run Behavior -- 5 Lyapunov Functions and Martingales -- 6 Eigenvalues and Nonhomogeneous Markov Chains -- 7 Gibbs Fields and Monte Carlo Simulation -- 8 Continuous-Time Markov Models -- 9 Poisson Calculus and Queues -- 1 Number Theory and Calculus -- 1.1 Greatest Common Divisor -- 1.2 Abel’s Theorem -- 1.3 Lebesgue’s Theorems for Series -- 1.4 Infinite Products -- 1.5 Tychonov’s Theorem -- 1.6 Subadditive Functions -- 2 Linear Algebra -- 2.1 Eigenvalues and Eigenvectors -- 2.2 Exponential of a Matrix -- 2.3 Gershgorin’s Bound -- 3 Probability -- 3.1 Expectation Revisited -- 3.2 Lebesgue’s Theorems for Expectation -- Author Index."]
[null,null,null,"Sommario/riassunto","In this book, the author begins with the elementary theory of Markov chains and very progressively brings the reader to the more advanced topics. He gives a useful review of probability that makes the book self-contained, and provides an appendix with detailed proofs of all the prerequisites from calculus, algebra, and number theory. A number of carefully chosen problems of varying difficulty are proposed at the close of each chapter, and the mathematics are slowly and carefully developed, in order to make self-study easier. The author treats the "]
[{"$nulls":4},"classic topics of Markov chain theory, both in discrete time and continuous time, as well as the connected topics such as finite Gibbs fields, nonhomogeneous Markov chains, discrete- time regenerative processes, Monte Carlo simulation, simulated annealing, and queuing theory. The result is an up-to-date textbook on stochastic processes. Students and researchers in operations research and electrical engineering, as well as in physics and biology, will find it very accessible and relevant."]