概率論與隨機過程(英文版) [Probability And Stochastic Processes] epub pdf  mobi txt 電子書 下載

概率論與隨機過程(英文版) [Probability And Stochastic Processes] epub pdf mobi txt 電子書 下載 2024

概率論與隨機過程(英文版) [Probability And Stochastic Processes] epub pdf mobi txt 電子書 下載 2024


簡體網頁||繁體網頁
張麗華,周清 編

下載链接在页面底部


點擊這裡下載
    


想要找書就要到 靜思書屋
立刻按 ctrl+D收藏本頁
你會得到大驚喜!!

發表於2024-06-25

商品介绍



齣版社: 北京郵電大學齣版社
ISBN:9787563545377
版次:1
商品編碼:11913846
包裝:平裝
叢書名: 普通高等教育“十二五”規劃教材
外文名稱:Probability And Stochastic Processes
開本:16開
齣版時間:2016-01-01
用紙:膠版紙
頁數:324
字數:54500

概率論與隨機過程(英文版) [Probability And Stochastic Processes] epub pdf mobi txt 電子書 下載 2024



类似图書 點擊查看全場最低價

相关書籍





書籍描述

內容簡介

  《概率論與隨機過程(英文版)》係統地介紹概率論與隨機過程的基本概念、基本方法、基本理論以及應用。《概率論與隨機過程(英文版)》分為8章。前4章介紹概率論的一般知識及應用,後四章介紹隨機過程的一般知識及應用。
  《概率論與隨機過程(英文版)》注重概念之間的聯係和背景介紹,強調知識的應用,而且《概率論與隨機過程(英文版)》所有內容是自包含的,講述淺顯易懂,便於自學。
  《概率論與隨機過程(英文版)》供非數學專業、應用型本科理工類一學期(64—72學時)學習使用。

目錄

Chapter 1 Events and Their Probabilities
1.1 The History of Probability
1.2 Experiment, Sample Space and Random Event
1.2.1 Basic Definitions
1.2.2 Events as Sets
1.3 Probabilities Defined on Events
1.3.1 Classical Probability
1.3.2 Geometric Probability
1.3.3 The Frequency Interpretation of Probability
1.4 Probability Space
1.4.1 Axiomatic Definition of Probability
1.4.2 Properties of Probability
1.5 Conditional Probabilities
1.5.1 The Definition of Conditional Probability
1.5.2 The Multiplication Rule
1.5.3 Total Probability Formula
1.5.4 Bayes' Theorem
1.6 Independence of Events
1.6.1 Independence of Two Events
1.6.2 Independence of Several Events
1.6.3 Bernoulli Trials
1.7 Review
1.8 Exercises

Chapter 2 Random Variable
2.1 The Definition of a Random Variable
2.2 The Distribution Function of a Random Variable
2.2.1 The Definition and Properties of Distribution Function . . .
2.2.2 The Distribution Function of Function of a Random Variable
2.3 Mathematical Expectation and Variance
2.3.1 Expectation of a Random Variable
2.3.2 Expectation of Functions of a Random Variable
2.3.3 Variance of a Random Variable
2.3.4 The Application cf Expectation and Variation
2.4 Discrete Random Variables
2.4.1 Binomial Distribution with Parameters n and p
2.4.2 Geometric Distribution
2.4.3 Poisscn Distribution with Parameters
2.5 Continuous Rsndom Variables
2.5.1 Uniform Distribution
2.5.2 Exponential Distribution
2.5.3 Normal Distribution
2.6 Review
2.7 Exerciscs

Chapter 3 Random Vectors
3.1 Random Vectors and Joint Distributions
3.1.1 Random Vectors and Joint Distributions
3.1.2 Discrete Random Vectors
3.1.3 Continuous Random Vectors
3.2 Independence cf Random Variables
3.3 Conditional Distributions
3.3.1 Discrete Case
3.3.2 Continuous Case
3.4 One Function of Two Random Variables
3.4.1 Discrete Case
3.4.2 Continuous case
3.5 Transformation of Two Random Variables
3.6 Numerical Charscteristics of Random Vectors
3.6.1 Expectation cf Sums and PIoducts
3.6.2 Covariance and Correlation
3.7 Multivariate Distributions
3.7.1 Distribution Functions of Multiple Random Vectors
3.7.2 Numerical Characteristics of Random Vectors
3.7.3 Multiple Normal Distribution
3.8 Review
3.9 Exercises

Chapter 4 Sequences of Random Variables
4.1 Family of Distribution Functions and Numerical Characteristics
4.2 Modes of Convergence
4.3 The Law of Large Numbers
4.4 The Central Limit Theorem
4.5 Review
4.6 Exercises

Chapter 5 Introduction to Stochastic Processes
5.1 Definition and Classification
5.2 The Distribution Family and the Moment Functions
5.3 The Moments of the Stochastic Processes
5.3.1 Mean, Autocorrelation and Autocovariance
5.3.2 Cross-correlation and Cross-covariance
5.4 Stochastic Analysis
5.5 Review
5.6 Exercises

Chapter 6 Stationary Processes
6.1 Stationary Processes
6.1.1 Strict Stationary Processes
6.1.2 Wide Stationary Processes
6.1.3 Joint Stationary Processes
6.2 Ergodicity of Stationary Processes
6.3 Power Spectral Density of Stationary Processes
6.3.1 Average Power and Power Spectral Density
6.3.2 Power Spectral Density and Autocorrelation Function
6.3.3 Cross-Power Spectral Density
6.4 Stationary Processes and Linear Systems
6.5 Review
6.6 Exercises

Chapter 7 Finite Markov Chains
7.1 Basic Concepts
7.2 Markov Chains Having Two States
7.3 Higher Order Transition Probabilities and Distributions
7.4 Invariant Distributions and Ergodic Markov Chain
7.5 How Does Google Work?
7.6 Review
7.7 Exercises

Chapter 8 Independent-Increment Processes
8.1 Independent-Increment Processes
8.2 Poisson Process
8.3 Gaussian Processes
8.4 Brownian Motion and Wiener Processes
8.5 Review
8.6 Exercises

Bibliography
Appendix
Table of Binomial Cofficients
Table of Binomial Probabilities
Table of Poisson Probabilities
Table of Normal Probabilities

概率論與隨機過程(英文版) [Probability And Stochastic Processes] epub pdf mobi txt 電子書 下載 2024

概率論與隨機過程(英文版) [Probability And Stochastic Processes] 下載 epub mobi pdf txt 電子書

概率論與隨機過程(英文版) [Probability And Stochastic Processes] pdf 下載 mobi 下載 pub 下載 txt 電子書 下載 2024

概率論與隨機過程(英文版) [Probability And Stochastic Processes] mobi pdf epub txt 電子書 下載 2024

概率論與隨機過程(英文版) [Probability And Stochastic Processes] epub pdf mobi txt 電子書 下載
想要找書就要到 靜思書屋
立刻按 ctrl+D收藏本頁
你會得到大驚喜!!

讀者評價

評分

評分

評分

評分

評分

評分

評分

評分

評分

概率論與隨機過程(英文版) [Probability And Stochastic Processes] epub pdf mobi txt 電子書 下載 2024

类似图書 點擊查看全場最低價

概率論與隨機過程(英文版) [Probability And Stochastic Processes] epub pdf mobi txt 電子書 下載 2024


分享鏈接





相关書籍


本站所有內容均為互聯網搜索引擎提供的公開搜索信息,本站不存儲任何數據與內容,任何內容與數據均與本站無關,如有需要請聯繫相關搜索引擎包括但不限於百度google,bing,sogou

友情鏈接

© 2024 book.tinynews.org All Rights Reserved. 靜思書屋 版权所有