出版时间:2007-11 出版社:清华大学出版社 作者:Anany Levitin 页数:562
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内容概要
本书采用了一种算法设计技术的新分类方法,不但比传统分类法包容性更强,而且更直观,也更有效,因此广受好评。 这种分类框架条理清晰,契合教育学原理,非常适合算法教学。网上提供了详尽的教学指南供教师和学生下载,书中还为学生安排了习题提示和每章小结。为了提高学习兴趣,书中应用了许多流行的谜题和游戏,需要重点思考的地方则往往会用反问来提醒注意。
作者简介
(美) Anany Levitin是Villanova大学计算科学系的教授。他的论文A New Road Map of Algorithm Design Techniques:Picking Up Where the Traditi。onal Classification Leaves Off(《算法设计技术新途径:弥补传统分类法的缺·感》)受到业内人士极高的评价。在SIGCSE会议
书籍目录
Preface1 Introduction 1.1 What is an Algorithm? Exercises 1.1 1.2 Fundamentals of Algorithmic Problem Solving Understanding the Problem Ascertaining the Capabilities of a Computational Device Choosing between Exact and Approximate Problem Solving Deciding on Appropriate Data Structures Algorithm Design Techniques Methods of Specifying an Algorithm Proving an Algorithm's Correctness Analyzing an Algorithm Coding an Algorithm Exercises 1.2 1.3 Important Problem Types Sorting Searching String Processing Graph Problems Combinatorial Problems Geometric Problems Numerical Problems Exercises 1.3 1.4 Fundamental Data Structures Linear Data Structures Graphs Trees Sets and Dictionaries Exercises 1.4 Summary2 Fundamentals of the Analysis of Algorithm Efficiency 2.1 Analysis Framework Measuring an Input's Size Units for Measuring Running -[]me Orders of Growth Worst-Case, Best-Case, and Average-Case Efficlencies Recapitulation of the Analysis Framework Exercises 2.1 2.2 Asymptotic Notations and Basic Efficiency Classes Informal Introduction O-notation 9-notation Onotation Useful Property Involving the Asymptotic Notations Using Limits for Comparing Orders of Growth Basic Efficiency Classes Exercises 2.2 2.3 Mathematical Analysis of Nonrecursive Algorithms Exercises 2.3 2.4 Mathematical Analysis of Recursive Algorithms Exercises 2.4 2.5 Example: Fibonacci Numbers Explicit Formula for the nth Fibonacci Number Algorithms for Computing Fibonacci Numbers Exercises 2.53 Brute Force4 Divide-and-Conquer5 Decrease-and-Conquer6 Transform-and-Conquer7 Space and lime Tradeoffs8 Dynamic Programming9 Greedy Technique10 Iterative Improvement11 Limitations of Algorithm Power12 Coping with the Limitations of Algorithm PowerEpilogueAPPENDIX AUseful Formulas for the Analysis of AlgorithmsAPPENDIX BShort Tutorial on Recurrence RelationsBibliographyHints to ExercisesIndex
编辑推荐
作者基于丰富的教学经验,开发了一套对算法进行分类的新方法。这套方法站在通用问题求解策略的高度,能对现有的大多数算法进行准确分类,从而使读者能够沿着一条清晰的、一致的、连贯的思路来探索算法设计与分析这一迷人领域。本书作为第2版,相对第1版增加了新的习题,还增加了“迭代改进”一章,使得原来的分类方法更加完善。本书十分适合作为算法设计和分析的基础教材,也适合任何有兴趣探究算法奥秘的读者使用,只要读者具备数据结构和离散数学的知识。本书为英文版。
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