Introduction to AlgorithmsMcGraw-Hill Higher Education, 1990 - 1028 Seiten This book provides a comprehensive introduction to the modern study of computer algorithms. It presents many algorithms and covers them in considerable depth, yet makes their design and analysis accessible to all levels of readers. We have tried to keep explanations elementary without sacrificing depth of coverage or mathematical rigor. Each chapter presents an algorithm, a design technique, an application area, or a related topic. Algorithms are described in English and in a "pseudocode" designed to be readable by anyone who has done a little programming. The book contains over 260 figrues illustrating how the algorithms work. Since we emphasize efficiency as a design criterion, we include careful analyses of the running times of all our algorithms. The text is intended primarily for use in undergraduate or graduate courses in algorithms or data structures. Because it discusses engineering issues in algorithm design, as well as mathematical aspects, it is equally well suited for self-study by technical professionals. -- |
Inhalt
Introduction | 1 |
Introduction | 21 |
Summations | 42 |
Urheberrecht | |
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Andere Ausgaben - Alle anzeigen
Introduction To Algorithms Thomas H Cormen,Charles E Leiserson,Ronald L Rivest,Clifford Stein Eingeschränkte Leseprobe - 2001 |
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
adder amortized cost assume asymptotic notation B-tree binary search tree binary tree binomial heap bitonic bits called Chapter circuit comparison sort compute constant contains data structure defined deletion denote depth depth-first search directed graph edge equation EREW example Exercise Fibonacci heap flow network function given graph G hash heapsort implementation induction input array insertion sort integer iteration key[x Lemma linear linked list loop lower bound matrix maximum merge sort method minimum multiplication O-notation O(lg O(n lg O(n² object operations optimal output partition performed permutation pointer polynomial probability problem procedure processor Proof prove pseudocode queue quicksort random variable real numbers red-black tree root list Section sequence shortest path Show solution solve sorting algorithm stack strongly connected component subarray subproblems subset subtree summation Suppose Theorem total number undirected upper bound vertex vertices weight worst-case running
Verweise auf dieses Buch
Multi-Objective Optimization using Evolutionary Algorithms Kalyanmoy Deb Eingeschränkte Leseprobe - 2001 |