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《应用随机过程》
应用随机过程
编号: PT239644
作者:林元烈
译者:
开本:16
ISBN:730205958
出版社:清华大学出版社
出版日期:2002-11-01
装帧:精装
书夫曼编号:487182
原价: 28
普通会员:26.18  一星会员:25.39
二星会员:24.87  三星会员:24.35

内容简介

本书是现代应用随机过程教材,内容从初等入门到现代前沿,包括预备知识、泊松过程、离散时间马尔可夫链、离散鞅、连续时间可尔可夫链、随机微分方程与宽平稳过程等8章。本书可供高等院校高年级学生与研究生作为教材使用,也可供教师及工程技术人员参考。                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  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目录

目      录  第1章    预备知识与随机过程的基本概念                                      1.  1    概率                                      1.  2    随机变量.  分布函数及数字特征                                      1.  3    矩母函数.  特征函数和拉普拉斯变换                                      1.  4    条件数学期望                                      1.  5    随机过程的概念                                      1.  6    随机过程的分类                                      练习题                                                                            第2章    泊松过程及其推广                                      2.  1    定义及其背景                                      2.  2    相邻事件的时间间隔,  泊松过程与指数分布的关系                                      2.  3    剩余寿命与年龄                                      2.  4    到达时间的条件分布                                      2.  5    泊松过程的模拟.  检验及参数估计                                      2.  6    非时齐泊松过程                                      2.  7    复合泊松过程                                      2.  8    条件泊松过程                                      2.  9    更新过程                                      2.  10    若干极限定理与基本更新定理                                      2.  11    更新方程与关键更新定理                                      练习题                                                                            第3章    马尔可夫链                                      3.  l    定义与例子                                      3.  2    转移概率矩阵                                      3.  3    状态的分类                                      3.  4    状态空间的分解                                      3.  5    Pn的极限性态与平稳分布                                      3.  6    离散时间的Phase-Type分布及其反问题                                      3.  7    首达目标模型与其他模型的关系                                      练习题                                                                            第4章    离散鞅引论                                      4.  1    定义与例子                                      4.  2    上鞅(下鞅)及分解定理                                      4.  3    停时与停时定理                                      4.  4    鞅收敛定理                                      4.  5    连续参数鞅                                      练习题                                                                            第5章    布朗运动                                      5.  l    随机游动与布朗运动的定义                                      5.  2    布朗运动轨道的性质                                      5.  3    首中时与最大值                                      5.  4    布朗桥                                      5.  5    布朗运动的各种变形与推广                                      5.  6    带有漂移的布朗运动                                      5.  7    n维布朗运动与牛顿位势                                      5.  8    用蒙特卡罗方法求解拉普拉斯方程                                      练习题                                                                            第6章    连续参数马尔可夫链                                      6.  1    定义与若干基本概念                                      6.  2    转移率矩阵--Q矩阵及其概率意义                                      6.  3    柯尔莫哥洛夫向前向后微分方程                                      6.  4    生灭过程                                      6.  5    强马尔可夫性与嵌入马尔可夫链                                      6.  6    连续参数马尔可夫链的随机模拟                                      6.  7    可逆马尔可夫链                                      6.  8    马尔可夫更新过程与半马尔可夫过程                                      6.  9    连续时间与离散时间的马尔可夫链首达目标模型间的关系                                      6.  10    首达时间与首达目标积分型泛函的待性及其反问题                                      练习题                                                                            第7章    随机微分方程                                      7.  1    H空间和均方收敛                                      7.  2    均方分析                                      7.  3    伊藤随机积分                                      7.  4    伊藤随机过程与伊藤公式                                      7.  5    伊藤随机微分方程                                      7.  6    解的存在性和唯一性问题                                      7.  7    解的基本特性与扩散过程                                      练习题                                                                            第8章    宽平稳过程                                      8.  1    宽平稳过程的定义和举例                                      8.  2    正态过程                                      8.  3    ARMA过程                                      8.  4    平稳过程的谱分解和协方差函数湘关函数)的港分解                                      8.  5    最佳均方预测与最佳线性均方预测                                      8.  6    各态历经性(遍历性)                                      8.  7    线性系统中的平稳过程                                      练习题                                      参考文献                                      索引


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