连续时间中的随机优化 epub pdf mobi txt 电子书 下载 2024

连续时间中的随机优化 epub pdf mobi txt 电子书 下载 2024

☆☆☆☆☆
简体网页||繁体网页



点击这里下载

连续时间中的随机优化 epub pdf mobi txt 电子书 下载 2024

类似图书 点击查看全场最低价

---

内容简介

　　"Stochastic optimization in continuous time"（AuthorFwu-Ranq Chang）is a rigorous but user-friendly book on the application of stochastic control theory to economics. A distinctive feature of the book is that math-ematical concepts are introduced in a language and terminology familiar to graduate students of economics.

目录

List of Figures
Preface
1 Probability Theory
1.1 Introduction
1.2 Stochastic Processes
1.2.1 In formation Sets and a -Algebras
1.2.2 The Cantor Set
1.2.3 Borel-Cantelli Lemmas
1.2.4 Distribution Functions and Stochastic Processes
1.3 Conditional Expectation
1.3.1 Conditional Probability
1.3.2 Conditional Expectation
1.3,3 Change of Variables
1.4 Notes and Further Readings
2 Wiener Processes
2.1 introduction
2.2 A Heuristic Approach
2.2.1 From Random Walks to Wiener Process
2.2.2 Some Basic Properties of the Wiener Process
2.3 Markov Processes
2.3.1 Introduction
2.3.2 Transition Probability
2.3.3 Diffusion Processes
2.4 Wiener Processes
2.4.1 How to Generate More Wiener Processes
2.4.2 Differentiability of Sample Functions
2.4.3 Stopping Times
2.4.4 The Zero Set
2.4.5 Bounded Variations and the Irregularity of the
Wiener Process
2.5 Notes and Further Readings
3 Stochastic Calculus
3.1 Introduction
3.2 A Heuristic Approach
3.2.1 ls □ （s X ）dWs Riemarm Integrable?
3.2.2 The Choice of□ Matters
3.2.3 In Search of the Class of Functions for a （s, w）
3.3 The Ito Integral
3.3.1 Definition
3.3.2 Martingales
3.4 lto's Lemma: Autonomous Case
3.4.1 Ito's Lemma
3.4.2 Geometric Brownian Motion
3.4.3 Population Dynamics
3.4.4 Additive Shocks or Multiplicative Shocks
3.4.5 Multiple Sources of Uncertainty
3.4.6 Multivariate lto's Lemma
3.5 Ito's Lemma for Time-Dependent Functions
3.5.1 Euler's Homogeneous Differential Equation and the Heat Equation
3.5.2 Black-Scholes Formula
3.5.3 Irreversible Investment
3.5.4 Budget Equation for an Investor
3.5.5 Ito's Lemma: General Form
3.6 Notes and Further Readings
4 Stochastic Dynamic Programming
4.1 Introduction
4.2 Bellman Equation
4.2.1 Infinite-Horizon Problems
4.2.2 Verification Theorem
4.2.3 Finite-Horizon Problems
4.2.4 Existence and Differentiability of the Value Function
4.3 Economic Applications
4.3.1 Consumption and Portfolio Rules
4.3.2 Index Bonds
4.3.3 Exhaustible Resources
4.3.4 Adjustment Costs and （Reversible） Investment
4.3.5 Uncertain Lifetimes and Life Insurance
4.4 Extension: Reeursive Utility
4.4.1 Bellman Equation with Recursive Utility
4.4.2 Effects of Reeursivity: Deterministic Case
4.5 Notes and Further Readings
5 How to Solve it
5.1 Introduction
5.2 HARA Functions
5.2.1 The Meaning of Each Parameter
5.2.2 Closed-Form Representations
5.3 Trial and Error
5.3.1 Linear-Quadratic Models
5.3.2 Linear-HARA models
5.3.3 Linear-Concave Models
5.3,4 Nonlinear-Concave Models
5.4 Symmetry
5.4.1 Linear-Quadratic Model Revisited
5.4.2 Merton's Model Revisited
5.4.3 Fischer's Index Bond Model
5.4.4 Life Insurance
5.5 The Substitution Method
5.6 Martingale Representation Method
5.6.1 Girsanov Transformation
5.6.2 Example: A Portfolio Problem
5.6.3 Which 8 to Choose?
5.6.4 A Transformed Problem
5.7 Inverse Optimum Method
5.7.1 The Inverse Optimal Problem: Certainty Case
5.7.2 The Inverse Optimal Problem: Stochastic Case
5.7.3 Inverse Optimal Problem of Merton's Model
5.8 Notes and Further Readings
6 Boundaries and Absorbing Barriers
6.1 Introduction
6.2 Nonnegativity Constraint
6.2.1 Issues and Problems
6.2.2 Comparison Theorems
6.2.3 Chang and Malliaris's Reflection Method
6.2.4 Inaccessible Boundaries
6.3 Other Constraints
6.3.1 A Portfolio Problem with Borrowing CoosWaints
6.3.2 Viscosity Solutions
6.4 Stopping Rules - Certainty Case
6.4.1 The Baumol-Tobin Model
6.4.2 A Dynamic Model of Money Demand
6.4.3 The Tree-Cutting Problem
6.5 The Expected Discount Factor
6.5.1 Fundamental Equation for Ex[e□]
6.5.2 One Absorbing Barrier
6.5.3 Two Absorbing Barriers
6.6 Optimal Stopping Times
6.6.1 Dynamic and Stochastic Demand for Money
6.6.2 Stochastic Tree-Cutting and Rotation Problems
6.6.3 Investment Timing
6.7 Notes and Further Readings
A Miscellaneous Applications and Exercises
Bibliography
Index

前言/序言

连续时间中的随机优化 epub pdf mobi txt 电子书 下载 2024

连续时间中的随机优化 下载 epub mobi pdf txt 电子书 2024

评分☆☆☆☆☆

无需波前传感器的像清晰化技术在不需要波前传感器的条件下，以成像清晰度和接受光能量为性能指标直接作为算法优化的目标函数，优化得到接近理想的校正效果，系统复杂性大大降低，比较适合用于补偿大气湍流带来的闪烁现象。

评分☆☆☆☆☆

在现代的管理科学、工程技术、社会经济、交通运输、金融保险等诸多领域都存在着大量的最优化问题。与此同时，这些领域又毋庸置疑地存在着人为的模糊性或客观的随机性。然而一个复杂的决策问题通常处在这两种不确定性因素混合的环境之中，模糊随机性就是一种具体的体现。那么，模糊随机环境下如何建立机会测度理论?如何建立单阶段和多阶段模糊随机优化模型?又如何采用逼近方法求解这些优化模型?本书分别回答了这些问题。该书将介绍模糊随机优化理论的最新研究成果，包括模糊随机环境下的平均机会理论、静态模糊随机规划、具有补偿问题的两阶段模糊随机规划、优化模型的逼近方法及其收敛性等问题。本书可作为应用数学专业高年级大学生和运筹学与控制论专业研究生教材，也可作为从事运筹学、管理科学及信息科学研究的高校教师和科技人员的参考书。

评分☆☆☆☆☆

评分☆☆☆☆☆

第一：由于不需要进行波前测量，系统中不需要采用波前传感器，也无需进行波前重构，而是以成像清晰度和接受光能量为性能指标直接作为算法优化的目标函数，降低了系统和算法的复杂性[3]。

评分☆☆☆☆☆

评分☆☆☆☆☆

应用背景

评分☆☆☆☆☆

编辑本段

评分☆☆☆☆☆

评分☆☆☆☆☆

第三：由于无需波前重构，大气湍流带来的闪烁不影响算法的迭代以及反馈装置的数据采集，在大气湍流较强或光束长程传输应用中有其独特优势[3]。

类似图书 点击查看全场最低价