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隨機過程導論：英文版

定　價：￥49.00

作　者：	（美）Edward P.C.Kao著
出版社：	機械工業(yè)出版社
叢編項：	經(jīng)典原版書庫
標　簽：	計算機/網(wǎng)絡影印版

購買這本書可以去

ISBN：	9787111124146	出版時間：	2003-01-01	包裝：	膠版紙
開本：	24cm	頁數(shù)：	438	字數(shù)：

內(nèi)容簡介

　　隨機過程是對隨時間和空間變化的隨機現(xiàn)象進行建模和分析的學科。許多年前，我們不能在現(xiàn)實問題求解中應用隨機過程，但隨著數(shù)值方法和計算工具的快速發(fā)展，這種狀況已經(jīng)發(fā)生了變化。本書很好地將計算機的使用和隨機過程教學結合起來，采用MATLAB的計算機解題方法，使本書充滿現(xiàn)代感，又具備實用的特點。本書采用面向應用和計算的方式，強調(diào)通過各種示例和習題來開發(fā)學生在隨機建模和分析中的實戰(zhàn)能力，同時將計算的任務交給計算機去完成。本書是為那些有興趣學習隨機過程的概念、模型和計算方法的學生編寫的，是隨機過程課程的入門教材，適合管理、金融、工程、統(tǒng)計、計算機科學和應用數(shù)學等專業(yè)的高年級本科生或低年級研究生閱讀本書前言特色及評論文章節(jié)選

作者簡介

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圖書目錄

1    Introduction  1
1.0  Overview  2
1.1  Introduction  2
1.2  Discrete Random Variables and Generating Functions  6
1.3  Continuous Random Variables and Laplace Transforms  17
1.4  Some Mathematical Background  28
Problems  37
Bibliographic Notes  42
References  43
Appendix  43
2  Poisson Processes  47
2.0  Overview  47
2.1  Introduction  48
2.2  Properties of Poisson Processes  51
2.3  Nonhomogeneous Poisson Processes  56
2.4  Compound Poisson Processes  72
2.5  Filtered Poisson Processes  76
2.6  Two-Dimensional and Marked Poisson Processes  80
2.1  Poisson Arrivals See Time Averages (PASTA)  83
Problems  87
Bibliographic Notes  93
References  94
Appendix  95
enewal Processes  97
3        3.0  Overview  97
3.1  Introduction  98
3.2  Renewal-Type Equations  101
3.3  Excess Life, Current Life, and Total Life  107
3.4  Renewal Reward Processes  118
3.5  Limiting Theorems, Stationary
and Transient Renewal Processes  128
3.6  Regenerative Processes  132
3.7  Discrete Renewal Processes  144
Problems  146
Bibliographic Notes  154
References  155
Appendix  156
iscrete-Time Markov Chains  160
4.0  Overview  160
4.1  Introduction  161
4.2  Classification of States  167
4.3  Ergodic and Periodic Markov Chains  175
4.4  Absorbing Markov Chains  188
4.5  Markov Reward Processes  203
4.6  Reversible Discrete-Tune Markov Chains  207
Problems 212
Bibliographic Notes  225
References  226
Appendix  227
ontinuous-Time Markov Chains  238
5.0  Overview  239
5.1  Introduction  239
5.2  The Kolmogorov Differential Equations  245
5.3  The Limiting Probabilities  252
5.4  Absorbing Continuous-Time Markov Chains  256
5.S  Phase-Type Distributions  264
5.6  Uniformization  273
5.7  Continuous-Time Markov Reward Processes  277
5.8  Reversible Continuous-Time Markov Chains  284
Problems  298
Bibliographic Notes  313
References  314
Appendix  316
arkov Renewal and Semi-Regenerative Processes  321
6.0  Overview  322
6.1  Introduction  322
6.2  Markov Renewal Functions and Equations  331
6.3  Semi-Markov Processes and Related Reward Processes  339
6.4  Semi-Regenerative Processes  348
Problems  363
Bibliographic Notes  367
References  367
Appendix  368
rownian Motion and Other Diffusion Processes  373
7.0  Overview  373
7.1  Introduction  374
7.2  Diffusion Processes  385
7.3  Ito's Calculus and Stochastic Differential Equations  396
7.4  Multidimensional Ito's Lemma  404
1.5  Control of Systems of Stochastic Differential Equations  409
Problems  417
Bibliographic Notes 419
References  420
Appendix  421
Appendix: Getting Started with MATLAB  427
Index  436