Introduction To AlgorithmsThe first edition won the award for Best 1990 Professional and Scholarly Book in Computer Science and Data Processing by the Association of American Publishers. There are books on algorithms that are rigorous but incomplete and others that cover masses of material but lack rigor. Introduction to Algorithms combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became the standard reference for professionals and a widely used text in universities worldwide. The second edition features new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming, as well as extensive revisions to virtually every section of the book. In a subtle but important change, loop invariants are introduced early and used throughout the text to prove algorithm correctness. Without changing the mathematical and analytic focus, the authors have moved much of the mathematical foundations material from Part I to an appendix and have included additional motivational material at the beginning. |
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LibraryThing Review
Nutzerbericht - IvanIdris - LibraryThingThis book is like an encyclopedia of algorithms. The algorithms are presented with pseudo code so it doesn’t matter what your favorite programming language is. A very rigorous mathematical approach is used for the analysis of for instance performance. Vollständige Rezension lesen
Inhalt
Introduction | 3 |
Getting Started | 15 |
Growth of Functions | 41 |
Recurrences | 62 |
Probabilistic Analysis and Randomized Algorithms | 91 |
Introduction | 123 |
Quicksort | 145 |
Sorting in Linear Time | 165 |
Data Structures for Disjoint Sets | 498 |
22 | 525 |
23 | 561 |
27 | 701 |
30 | 822 |
String Matching | 906 |
Computational Geometry | 933 |
NPCompleteness | 966 |
Medians and Order Statistics | 183 |
Introduction | 197 |
Hash Tables | 221 |
Introduction | 321 |
18 | 431 |
Binomial Heaps | 455 |
Fibonacci Heaps | 476 |
Approximation Algorithms | 1022 |
Introduction | 1057 |
B Sets Etc | 1070 |
Counting and Probability | 1094 |
1127 | |
1145 | |
Andere Ausgaben - Alle anzeigen
Introduction to Algorithms (Instructor's Manual) Thomas H. Cormen,Charles E. Leiserson,Ronald L. Rivest,Clifford Stein Keine Leseprobe verfügbar - 2014 |
Introduction to Algorithms and Java CD-ROM Thomas Cormen,Charles Leiserson,Ronald Rivest,Clifford Stein Keine Leseprobe verfügbar - 2003 |
Introduction to Algorithms and Java CD-ROM Thomas Cormen,Charles Leiserson,Ronald Rivest,Clifford Stein Keine Leseprobe verfügbar - 2003 |
Häufige Begriffe und Wortgruppen
algorithm amortized analysis application array assume asymptotic basic binary search tree bound Chapter comparator comparison compute consider constant constraints contains corresponding cost cycle data structure define DELETE denote Describe determine directed edge efficient elements equal equation example execution Exercise exists expected factor feasible Figure flow function Give given graph G hash heap implement increasing initial input insertion integer iteration least Lemma length linear program linked loop matrix maximum method multiplication node Note objective operations optimal output pair performed pointer points polynomial positive problem procedure produce Proof prove random recursive represent requires result root running sequence shortest path shown solution solve sort step stored subproblems subtree Suppose takes Theorem tree variables vertex vertices weight
Verweise auf dieses Buch
Multi-Objective Optimization using Evolutionary Algorithms Kalyanmoy Deb Eingeschränkte Leseprobe - 2001 |