語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Markov chains = Gibbs fields, Monte ...
~
Bremaud, Pierre.
FindBook
Google Book
Amazon
博客來
Markov chains = Gibbs fields, Monte Carlo simulation and queues /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Markov chains/ by Pierre Bremaud.
其他題名:
Gibbs fields, Monte Carlo simulation and queues /
作者:
Bremaud, Pierre.
出版者:
Cham :Springer International Publishing : : 2020.,
面頁冊數:
xvi, 557 p. :ill., digital ;24 cm.
內容註:
Preface -- 1 Probability Review -- 2 Discrete-Time Markov Chains -- 3 Recurrence and Ergodicity -- 4 Long-Run Behavior -- 5 Discrete-Time Renewal Theory -- 6 Absorption and Passage Times -- 7 Lyapunov Functions and Martingales -- 8 Random Walks on Graphs -- 9 Convergence Rates -- 10 Markov Fields on Graphs -- 11 Monte Carlo Markov Chains -- 12 Non-homogeneous Markov Chains -- 13 Continuous-Time Markov Chains -- 14 Markovian Queueing Theory -- Appendices -- Bibliography -- Index.
Contained By:
Springer eBooks
標題:
Markov processes. -
電子資源:
https://doi.org/10.1007/978-3-030-45982-6
ISBN:
9783030459826
Markov chains = Gibbs fields, Monte Carlo simulation and queues /
Bremaud, Pierre.
Markov chains
Gibbs fields, Monte Carlo simulation and queues /[electronic resource] :by Pierre Bremaud. - Second edition. - Cham :Springer International Publishing :2020. - xvi, 557 p. :ill., digital ;24 cm. - Texts in applied mathematics,v.310939-2475 ;. - Texts in applied mathematics ;v.31..
Preface -- 1 Probability Review -- 2 Discrete-Time Markov Chains -- 3 Recurrence and Ergodicity -- 4 Long-Run Behavior -- 5 Discrete-Time Renewal Theory -- 6 Absorption and Passage Times -- 7 Lyapunov Functions and Martingales -- 8 Random Walks on Graphs -- 9 Convergence Rates -- 10 Markov Fields on Graphs -- 11 Monte Carlo Markov Chains -- 12 Non-homogeneous Markov Chains -- 13 Continuous-Time Markov Chains -- 14 Markovian Queueing Theory -- Appendices -- Bibliography -- Index.
This 2nd edition is a thoroughly revised and augmented version of the book with the same title published in 1999. The author begins with the elementary theory of Markov chains and very progressively brings the reader to more advanced topics. He gives a useful review of probability, making 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 is slowly and carefully developed, in order to make self-study easier. The book treats the classical topics of Markov chain theory, both in discrete time and continuous time, as well as connected topics such as finite Gibbs fields, nonhomogeneous Markov chains, discrete-time regenerative processes, Monte Carlo simulation, simulated annealing, and queuing theory. The main additions of the 2nd edition are the exact sampling algorithm of Propp and Wilson, the electrical network analogy of symmetric random walks on graphs, mixing times and additional details on the branching process. The structure of the book has been modified in order to smoothly incorporate this new material. Among the features that should improve reader-friendliness, the three main ones are: a shared numbering system for the definitions, theorems and examples; the attribution of titles to the examples and exercises; and the blue highlighting of important terms. 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.
ISBN: 9783030459826
Standard No.: 10.1007/978-3-030-45982-6doiSubjects--Topical Terms:
532104
Markov processes.
LC Class. No.: QA274.7 / .B733 2020
Dewey Class. No.: 519.233
Markov chains = Gibbs fields, Monte Carlo simulation and queues /
LDR
:03299nmm a2200361 a 4500
001
2255342
003
DE-He213
005
20201007135251.0
006
m d
007
cr nn 008maaau
008
220419s2020 sz s 0 eng d
020
$a
9783030459826
$q
(electronic bk.)
020
$a
9783030459819
$q
(paper)
024
7
$a
10.1007/978-3-030-45982-6
$2
doi
035
$a
978-3-030-45982-6
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA274.7
$b
.B733 2020
072
7
$a
PBT
$2
bicssc
072
7
$a
MAT029000
$2
bisacsh
072
7
$a
PBT
$2
thema
072
7
$a
PBWL
$2
thema
082
0 4
$a
519.233
$2
23
090
$a
QA274.7
$b
.B836 2020
100
1
$a
Bremaud, Pierre.
$3
532103
245
1 0
$a
Markov chains
$h
[electronic resource] :
$b
Gibbs fields, Monte Carlo simulation and queues /
$c
by Pierre Bremaud.
250
$a
Second edition.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2020.
300
$a
xvi, 557 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Texts in applied mathematics,
$x
0939-2475 ;
$v
v.31
505
0
$a
Preface -- 1 Probability Review -- 2 Discrete-Time Markov Chains -- 3 Recurrence and Ergodicity -- 4 Long-Run Behavior -- 5 Discrete-Time Renewal Theory -- 6 Absorption and Passage Times -- 7 Lyapunov Functions and Martingales -- 8 Random Walks on Graphs -- 9 Convergence Rates -- 10 Markov Fields on Graphs -- 11 Monte Carlo Markov Chains -- 12 Non-homogeneous Markov Chains -- 13 Continuous-Time Markov Chains -- 14 Markovian Queueing Theory -- Appendices -- Bibliography -- Index.
520
$a
This 2nd edition is a thoroughly revised and augmented version of the book with the same title published in 1999. The author begins with the elementary theory of Markov chains and very progressively brings the reader to more advanced topics. He gives a useful review of probability, making 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 is slowly and carefully developed, in order to make self-study easier. The book treats the classical topics of Markov chain theory, both in discrete time and continuous time, as well as connected topics such as finite Gibbs fields, nonhomogeneous Markov chains, discrete-time regenerative processes, Monte Carlo simulation, simulated annealing, and queuing theory. The main additions of the 2nd edition are the exact sampling algorithm of Propp and Wilson, the electrical network analogy of symmetric random walks on graphs, mixing times and additional details on the branching process. The structure of the book has been modified in order to smoothly incorporate this new material. Among the features that should improve reader-friendliness, the three main ones are: a shared numbering system for the definitions, theorems and examples; the attribution of titles to the examples and exercises; and the blue highlighting of important terms. 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.
650
0
$a
Markov processes.
$3
532104
650
1 4
$a
Probability Theory and Stochastic Processes.
$3
891080
650
2 4
$a
Operations Research/Decision Theory.
$3
890895
650
2 4
$a
Electrical Engineering.
$3
1001838
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
830
0
$a
Texts in applied mathematics ;
$v
v.31.
$3
3524859
856
4 0
$u
https://doi.org/10.1007/978-3-030-45982-6
950
$a
Mathematics and Statistics (Springer-11649)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9410981
電子資源
11.線上閱覽_V
電子書
EB QA274.7 .B733 2020
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入