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凸优化txt，chm，pdf，epub，mobi下载作者: Stephen Boyd / Lieven Vandenberghe 出版社: 世界图书出版公司北京公司 副标题: Convex Potimization 出版年: 2013-10-1 页数: 716 定价: 149.00 装帧: 平装 ISBN: 9787510061356 内容简介 · · · · · ·《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 · · · · · ·PrefaceIntroduction 1.1. Mathematical optimization 1.2 Least—squares and linear programming 1.3 Convex optimization 1.4 Nonlinear optimization · · · · · · () 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 · · · · · · () |
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作者： 你是会闪光的星
文字却通俗易懂
提供了很多清晰的论点
需要静下心慢慢看
怎么说呢，感觉这本书涉及的方方面面太多