| | | 復雜性理論 | 該商品所屬分類:自然科學 -> 自然科學 | 【市場價】 | 732-1062元 | 【優惠價】 | 458-664元 | 【作者】 | (德)韋格納(IngoW) | 【所屬類別】 | 圖書 自然科學 數學 數學理論 | 【出版社】 | 科學出版社有限責任公司 | 【ISBN】 | 9787030166920 | 【折扣說明】 | 一次購物滿999元台幣免運費+贈品 一次購物滿2000元台幣95折+免運費+贈品 一次購物滿3000元台幣92折+免運費+贈品 一次購物滿4000元台幣88折+免運費+贈品
| 【本期贈品】 | ①優質無紡布環保袋,做工棒!②品牌簽字筆 ③品牌手帕紙巾
| |
版本 | 正版全新電子版PDF檔 | 您已选择: | 正版全新 | 溫馨提示:如果有多種選項,請先選擇再點擊加入購物車。*. 電子圖書價格是0.69折,例如了得網價格是100元,電子書pdf的價格則是69元。 *. 購買電子書不支持貨到付款,購買時選擇atm或者超商、PayPal付款。付款後1-24小時內通過郵件傳輸給您。 *. 如果收到的電子書不滿意,可以聯絡我們退款。謝謝。 | | | | 內容介紹 | |
![](http://img3m2.ddimg.cn/98/11/23933942-1_u_4.jpg)
開本:16開 紙張:膠版紙 包裝:精裝 是否套裝:否 國際標準書號ISBN:9787030166920 叢書名:國外數學名著繫列(影印版) 作者:(德)韋格納(Ingo,W.) 出版社:科學出版社有限責任公司 出版時間:2006年01月 
" 目錄 Contents 1 Introduction 1 1.1 What Is Complexity Theory 1 1.2 Didactic Background 5 1.3 Overview 6 1.4 Additional Literature 10 2 Algorithmic Problems Their Complexity 11 2.1 What Are Algorithmic Problems 11 2.2 Some Important Algorithmic Problems 13 2.3 Measuring Computation Time 18 2 4 The Complexity of Algorithmic Problems 22 3 Fundamental Complexity Classes 25 3.1 The Special Role of Polynomial Computation Time 25 3.2 Ra ndomized Algorithms 27Contents 1 Introduction 1 1.1 What Is Complexity Theory 1 1.2 Didactic Background 5 1.3 Overview 6 1.4 Additional Literature 10 2 Algorithmic Problems & Their Complexity 11 2.1 What Are Algorithmic Problems 11 2.2 Some Important Algorithmic Problems 13 2.3 Measuring Computation Time 18 2 4 The Complexity of Algorithmic Problems 22 3 Fundamental Complexity Classes 25 3.1 The Special Role of Polynomial Computation Time 25 3.2 Ra ndomized Algorithms 27 3.3 The Fundamental Complexity Classes for Algorithmic Problems 30 3.4 The Fundamental Complexity Classes for Decision Problems 35 3.5 Nondeterminism as a Special Case of Ra ndomization 39 4 Reductions - AIgorithmic Relationships Between Problems 43 4.1 When Are Two Problems AIgorithmically Similar 43 4.2 Reductions Between Various Variants of a Problem 46 4.3 Reductions Between Rβlated Problems 49 4.4 Rβductions Between Unrelated Problems 53 4.5 The Special Role of Polynomial Reductions 60 5 The Theory of NP-Completeness 63 5.1 Fundamental Considerations 63 5.2 Problems in NP 67 5 3 Alternative Characteriz ations of NP 69 5 4 Cook's Theorem 70 6 NP-complete and NP-equivalent Problems 77 6.1 Fundamental Considerations 77 6.2τ'raveling Salesperson Problems 77 6.3 Knapsack Problems 78 6.4 Partitioning and Scheduling Problems 80 6.5 Clique Problems 81 6.6 Team Building Problems 83 6.7 Championship Problems 85 7 The Complexity Analysis of Problems 89 7.1 The Dividing Line Between Easy and Hard 89 7.2 Pseudo-polynomial Algorithms and Strong NP-completeness 93 7.3 An Overview of the NP-completeness Proofs Considered 96 8 The Complexity of Approximation Problems – Classical Results 99 8.1 Complexity Classes 99 8.2 Approximation Algorithms 103 8.3 The Gap Technique 106 8.4 Approximation-Preserving Rβductions 109 8.5 Complete Approximation Problems 112 9 The Complexity of Black Box Problems 115 9.1 Black Box Optimization 115 9.2 Yao's Minimax Principle 118 9.3 Lower Bounds for Black Box Complexity 120 10 Additional Complexity Classes 127 10.1 Fundamental Considerations 127 10.2 Complexity Classes Within NP and co-NP 128 10.3 Oracle Classes 130 10.4 The Polynomial Hierarchy 132 10.5 BPP, NP, and the Polynomial Hierarchy 138 11 Interactive Proofs 145 11.1 Fundamental Considerations 145 11.2 Interactive Proof Systems 147 11.3 Rβgarding the Complexity of Graph Isomorphism Problems 148 11.4 ZerφKnowledge Proofs 155 12 The PCP Theorem and the Complexity of Approximation Problems 161 12.1 Randomized Verification of Proofs 161 12.2 The PCP Theorem 164 12.3 The PCP Theorem and Inapproximability Rβsults 173 12.4 The PCP Theorem and APX-Completeness 177 13 Further Topics From Classical Complexity Theory 185 13.1 Overview 185 13.2 SpacφBounded Complexity Classes 186 13.3 PSPACE-complete Problems 188 13.4 Nondeterminism and Determinism in the Context of Bounded Space 191 13.5 Nondeterminism and Complementation with Precise Space Bounds 193 13.6 Complexity Classes Within P 195 13.7 The Complexity of Counting Problems 198 14 The Complexity of Non-uniform Problems 201 14.1 Fundamental Considerations 201 14.2 The Simulation of Turing Machines By Circuits 204 14.3 The Simulation of Circuits by Non-uniform Turing Machines 206 14.4 Branching Programs and Space Bounds 209 14.5 Polynomial Circuits for Problems in BPP 211 14.6 Complexity Classes for Computation with Help 212 14.7 Are There Polynomial Circuits for all Problems in NP 214 15 Communication Complexity 219 15.1 The Communication Game 219 15.2 Lower Bounds for Communication Complexity 223 15.3 Nondeterministic Communication Protocols 233 15.4 Randomized Communication Protocols 238 15.5 Communication Complexity and VLSI Circuits 246 15.6 Communication Complexity and Computation Time 247 16 The Complexity of Boolean Functions 251 16.1 Fundamental Considerations 251 16.2 Circuit Size 252 16.3 Circuit Depth 254 16.4 The Size of Depth-Bounded Circuits 259 16.5 The Size of Depth-Bounded Threshold Circuits 264 16.6 The Size of Branching Programs 267 16.7 Reduction Notions 271 Final Comments 277 A Appendix 279 A.1 Orders of Magnitude and O-Notation 279 A.2 Results from Probability Theory 283 References 295 Index 301 | | | | | |