Sale!

Theory of computational complexity 2nd Edition by Dingzhu Du, Ker I Ko ISBN 1118594975 9781118594971

Original price was: $50.00.Current price is: $35.00.

Theory of computational complexity 2nd ed Edition Du Digital Instant Download

Author(s): Du, Dingzhu;Ko, Ker-I
ISBN(s): 9781118594971, 1118594975
Edition: 2nd ed
File Details: PDF, 3.27 MB
Year: 2014
Language: english
SKU: EB-11794506 Category: Tags: , , ,

Theory of computational complexity 2nd Edition by Dingzhu Du, Ker I Ko – Ebook PDF Instant Download/Delivery: 1118594975, 9781118594971
Full download Theory of computational complexity 2nd Edition after payment

Product details:

ISBN 10: 1118594975 
ISBN 13: 9781118594971
Author: Dingzhu Du, Ker I Ko

Praise for the First Edition “…complete, up-to-date coverage of computational complexity theory…the book promises to become the standard reference on computational complexity.” -Zentralblatt MATH A thorough revision based on advances in the field of computational complexity and readers’ feedback, the Second Edition of Theory of Computational Complexity presents updates to the principles and applications essential to understanding modern computational complexity theory. The new edition continues to serve as a comprehensive resource on the use of software and computational approaches for solving algorithmic problems and the related difficulties that can be encountered. Maintaining extensive and detailed coverage, Theory of Computational Complexity, Second Edition, examines the theory and methods behind complexity theory, such as computational models, decision tree complexity, circuit complexity, and probabilistic complexity. The Second Edition also features recent developments on areas such as NP-completeness theory, as well as: A new combinatorial proof of the PCP theorem based on the notion of expander graphs, a research area in the field of computer science Additional exercises at varying levels of difficulty to further test comprehension of the presented material End-of-chapter literature reviews that summarize each topic and offer additional sources for further study  Theory of Computational Complexity, Second Edition, is an excellent textbook for courses on computational theory and complexity at the graduate level. The book is also a useful reference for practitioners in the fields of computer science, engineering, and mathematics who utilize state-of-the-art software and computational methods to conduct research. A thorough revision based on advances in the field of computational complexity and readers’ feedback, the Second Edition of Theory of Computational Complexity presents updates to the principles and applications essential to understanding modern computational complexity theory. The new edition continues to serve as a comprehensive resource on the use of software and computational approaches for solving algorithmic problems and the related difficulties that can be encountered. Maintaining extensive and detailed coverage, Theory of Computational Complexity, Second Edition, examines the theory and methods behind complexity theory, such as computational models, decision tree complexity, circuit complexity, and probabilistic complexity. The Second Edition also features recent dev

Theory of computational complexity 2nd Table of contents:

Part I: Uniform Complexity
Chapter 1: Models of Computation and Complexity Classes
1.1 Strings, Coding, and Boolean Functions
1.2 Deterministic Turing Machines
1.3 Nondeterministic Turing Machines
1.4 Complexity Classes
1.5 Universal Turing Machine
1.6 Diagonalization
1.7 Simulation
Exercises
Historical Notes
Chapter 2: NP-Completeness
2.1 NP
2.2 Cook’s Theorem
2.3 More NP-Complete Problems
2.4 Polynomial-Time Turing Reducibility
2.5 NP-Complete Optimization Problems
Exercises
Historical Notes
Chapter 3: The Polynomial-Time Hierarchy and Polynomial Space
3.1 Nondeterministic Oracle Turing Machines
3.2 Polynomial-Time Hierarchy
3.3 Complete Problems in PH
3.4 Alternating Turing Machines
3.5 PSPACE-Complete Problems
3.6 EXP-Complete Problems
Exercises
Historical Notes
Chapter 4: Structure of NP
4.1 Incomplete Problems in NP
4.2 One-Way Functions and Cryptography
4.3 Relativization
4.4 Unrelativizable Proof Techniques
4.5 Independence Results
4.6 Positive Relativization
4.7 Random Oracles
4.8 Structure of Relativized NP
Exercises
Historical Notes
Part II: Nonuniform Complexity
Chapter 5: Decision Trees
5.1 Graphs and Decision Trees
5.2 Examples
5.3 Algebraic Criterion
5.4 Monotone Graph Properties
5.5 Topological Criterion
5.6 Applications of the Fixed Point Theorems
5.7 Applications of Permutation Groups
5.8 Randomized Decision Trees2
5.9 Branching Programs
Exercises
Historical Notes
Chapter 6: Circuit Complexity
6.1 Boolean Circuits
6.2 Polynomial-Size Circuits
6.3 Monotone Circuits
6.4 Circuits with Modulo Gates
6.5 NC
6.6 Parity Function
6.7 P-Completeness
6.8 Random Circuits and RNC
Exercises
Historical Notes
Chapter 7 Polynomial-Time Isomorphism
7.1 Polynomial-Time Isomorphism
7.2 Paddability
7.3 Density of NP-Complete Sets
7.4 Density of EXP-Complete Sets
7.5 One-Way Functions and Isomorphism in EXP
7.6 Density of P-Complete Sets
Exercises
Historical Notes
Part III: Probabilistic Complexity
Chapter 8: Probabilistic Machines and Complexity Classes
8.1 Randomized Algorithms
8.2 Probabilistic Turing Machines
8.3 Time Complexity of Probabilistic Turing Machines
8.4 Probabilistic Machines with Bounded Errors
8.5 BPP and P
8.6 BPP and NP
8.7 BPP and the Polynomial-Time Hierarchy
8.8 Relativized Probabilistic Complexity Classes
Exercises
Historical Notes
Chapter 9: Complexity of Counting
9.1 Counting Class
9.2 -Complete Problems
9.3 and the Polynomial-Time Hierarchy
9.4 and the Polynomial-Time Hierarchy
9.5 Circuit Complexity and Relativized and
9.6 Relativized Polynomial-Time Hierarchy
Exercises
Historical Notes
Chapter 10: Interactive Proof Systems
10.1 Examples and Definitions
10.2 Arthur–Merlin Proof Systems
10.3 AM Hierarchy Versus Polynomial-Time Hierarchy
10.4 IP Versus AM
10.5 IP Versus PSPACE
Exercises
Historical Notes
Chapter 11: Probabilistically Checkable Proofs and NP-Hard Optimization Problems
11.1 Probabilistically Checkable Proofs
11.2 PCP Characterization of NP
11.3 Probabilistic Checking and Inapproximability
11.4 More NP-Hard Approximation Problems

People also search for Theory of computational complexity 2nd:

    
theory of computational complexity pdf
    
computational complexity of density functional theory
    
some applications of coding theory in computational complexity
    
what is computational theory
    
what is computational complexity

Tags: Dingzhu Du, Ker I Ko, computational complexity