Computer science, algorithms and complexity /

Бібліографічні деталі
Інші автори:	Kuzmiakova, Adele
Формат:	Licensed eBooks
Мова:	Англійська
Опубліковано:	Burlington, ON : Arcler Press, 2020.
Онлайн доступ:	https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2725240

Зміст:

Cover
Title Page
Copyright
ABOUT THE EDITOR
TABLE OF CONTENTS
List of Figures
List of Tables
List of Abbreviations
Preface
Chapter 1 Basic Techniques for Design and Analysis of Algorithms
1.1. Introduction
1.2. Divide-And-Conquer Algorithms
1.3 Dynamic Programming
1.4. Greedy Heuristics
1.5. Sentinel Linear Search
1.6. Backtracking
1.7. Brute Force/Exhaustive Search
1.8. Branch-And-Bound Algorithm
1.9. Randomized Algorithm
1.10. Branch-H And-Bound
Chapter 2 Computational Complexity Theory
2.1. Introduction
2.2. Brief History
2.3. Computation Models
2.4. Turing Machines
2.5. Computational Problems
2.6. Complexity Classes
2.7. Relationships Between Complexity Classes
2.8. Reducibility And Completeness
2.9. Relativization of P Vs. Np Problem
2.10. Polynomial Hierarchy
2.11. Alternating Complex Classes
2.12. Circuit Complexity
2.13. Probabilistic Complexity Classes
2.14. Interactive Models And Complexity Classes
2.15. Kolmogorov Complexity
Chapter 3 Graph and Network Algorithms
3.1. Introduction
3.2. Tree Traversals
3.3. Depth-First Search
3.4. Algorithm
3.5. Minimum Spanning Trees
Chapter 4 Cryptography
4.1. Introduction
4.2. Quantum Cryptography
4.3. Transmission Media
4.4. History Of Cryptography
4.5. Cryptography Notions Of Security
4.6. Cryptography Building Blocks
4.7. Benefits Of Cryptography
4.8. Drawbacks Of Cryptography
Chapter 5 Algebraic Algorithms
5.1. Introduction
5.2. Computational Methods
5.3. Systems Of Nonlinear Equations And Their Applications
5.4. Polynomial Factorization
Chapter 6 Parallel Algorithms
6.1. Introduction
6.2. Parallelizability
6.3. Dispersed Algorithms
6.4. Parallel Programming Models
6.5. Parallel Algorithm Techniques
6.6. Graphs
6.7. Sorting
6.8. Computational Geometry
6.9. Numerical Algorithms
Chapter 7 Randomized Algorithms
7.1. Introduction
7.2. The Basic Principles Underlying The Construction Of Randomized Algorithms
7.3. Randomized Increasing Constructions In Geometry
7.4. Algorithm Analysis
7.5. De-Randomization
7.6. Example Where Randomness Helps
Chapter 8 Pattern Matching And Text Compression Algorithms
8.1. Introduction
8.2. Processing Texts Efficiently
8.3. Choosing Ml Algorithms
8.4. String-Matching Algorithms
8.5. Two-Dimensional Pattern Matching Algorithms
8.6. Suffix Trees
8.7. Alignment
8.8. Approximate Strinng
8.9. Text Compression
8.10. Research Issues And Summary
8.11. Searching Compressed Dat
Chapter 9 Genetic Algorithms
9.1. Introduction
9.2. Initialization
9.3. Selection
9.4. Genetic Operations
9.5. Heuristics Method
9.6. Termination
9.7. Examples Of Genetic Algorithms
9.8. Underlying Principles In Genetic Algorithm
9.9. Genetic Parameters
9.10. Best Practices In Genetic Algorithm

Computer science, algorithms and complexity /

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