凸优化

出版者:世界图书出版公司北京公司

作者:Stephen Boyd

页数:716

出版时间:2013-10-1

价格:149.00

装帧:平装

isbn号码:9787510061356

具体描述

《凸优化(英文)》由世界图书出版社出版。

作者简介

作者：（美国）鲍迪（Stephen Boyd）

目录信息

Preface
Introduction
1.1. Mathematical optimization
1.2 Least—squares and linear programming
1.3 Convex optimization
1.4 Nonlinear optimization
1.5 Outline
1.6 Notation
Bibliography
Theory
Convex sets
2.1 Affine and convex sets
2.2 Some important examples
2.3 Operations that preserve convexity
2.4 Generalized inequalities
2.5 Separating and supporting hyperplanes
2.6 Dual cones and generalized inequalities
Bibliography
Exercises
Convex functions
3.1 Basic properties and examples
3.2 Operations that preserve convexity
3.3 The conjugate function
3.4 Quasiconvex functions
3.5 Log—concave and log—convex functions
3.6 Convexity with respect to generalized inequalities
Bibliography
Exercises
Convex optimization problems
4.1 Optimization problems
4.2 Convex optimization
4.3 Linear optimization problems
4.4 Quadratic optimization problems
4.5 Geometric programming
4.6 Generalized inequality constraints
4.7 Vector optimization
Bibliography
Exercises
Duality
5.1 The Lagrange dual function
5.2 The Lagrange dual problem
5.3 Geometric interpretation
5.4 Saddle—point interpretation
5.5 Optimality conditions
5.0 Perturbation and sensitivity analysis
5.7 Examples
5.8 Theorems of alternatives
5，9 Generalized inequalities
Bibliography
Exercises
II Applications
6 Approximation and fitting
6.1 Norm approximation
0.2 Least—norm problems
6.3 Regularized approximation
6.4 Robust approximation
6.5 Function fitting and interpolation
Bibliography
Exercises
Statistical estimation
7.1 Parametric distribution estimation
7.2 Nonparametric distribution estimation
7.3 Optimal detector design and hypothesis testing
7.4 Chebyshev and Chernoff bounds
7.5 Experiment design
Bibliography
Exercises
8 Geometric problems
8.1 Projection on a set
8.2 Distance between sets
8.3 Euclidean distance and angle problems
8.4 Extremal volume ellipsoids
8.5 Centering
8.6 Classification
8.7 Placement and location
8.8 Floor planning
Bibliography
Exercises
III Algorithms
9 Unconstrained minimization
9.1 Unconstrained minimization problems
9.2 Descent methods
9.3 Gradient descent method
9.4 Steepest descent method
9.5 Newton's method
9.6 Self—concordance
9.7 Implementation
Bibliography
Exercises
10 Equality constrained minimization
10.1 Equality constrained minimization problems
10.2 Newton's method with equality constraints
10.3 Infeasible start Newton method
10.4 Implementation
Bibliography
Exercises
11 Interior—point methods
11.1 Inequality constrained minimization problems
11.2 Logarithmic barrier function and central path
11.3 The barrier method
11.4 Feasibility and phase I methods
11.5 Complexity analysis via self—concordance
11.6 Problems with generalized inequalities
11.7 Primal—dual interior—point methods
11.8 Implementation
Bibliography
Exercises
Appendices
A Mathematical background
A.1 Norms
A.2 Analysis
A.3 Functions
A.4 Derivatives
A.5 Linear algebra
Bibliography
B Problems involving two quadratic functions
B.1 Single constraint quadratic optimization
B.2 The S—procedure
B.3 The field of values of two symmetric matrices
B.4 Proofs of the strong duality results
Bibliography
C Numerical linear algebra background
C.1 Matrix structure and algorithm complexity
C.2 Solving linear equations with factored matrices
C.3 LU， Cholesky， and LDLT factorization
C.4 Block elimination and Schur complements
C.5 Solving underdetermined linear equations
Bibliography
References
Notation
Index
· · · · · · (收起)

读后感

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看起来是厚厚的一本大部头，读起来并不太费力。它给出的实例多而好用、覆盖面全，不需要太深刻的数学功底，对于复杂的定理性质等也不强调证明，而是着眼于几何意义和实际用途，直观易懂。 作者本身的工科背景使得这本书在工业问题和计算机等实用方面的优点更为突出，数学依据...  

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强大的数学工具----凸优化！ 用于解决很多工程问题 无数科学研究者在这上面砸无数文章 这本书是对凸优化最全面的介绍 但是阅读前最好有较好的矩阵论运算的基础 比如向量分解，特征值分解等等 学完此书再看些文章可以感觉你真正学到了东西！！  

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凸优化

内容详实，凸优化领域入门书，不过读起来略微啰嗦，很多内容缺乏严格证明。

凸优化

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凸优化