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算法设计技巧与分析-英文版

算法设计技巧与分析-英文版

出版社:电子工业出版社出版时间:2013-06-01
开本: 大32开 页数: 523
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算法设计技巧与分析-英文版 版权信息

算法设计技巧与分析-英文版 本书特色

  本书是国际著名算法专家李德财教授主编的系列丛书“lecture notes series on computing”中的一本。本书涵盖了绝大多数算法设计中的一般技术,在表达每一种技术时,阐述它的应用背景,注意用与其他技术比较的方法说明它的特征,并提供大量相应实际问题的例子。全书分七部分19章,从算法设计和算法分析的基本概念和方法入手,先后介绍了递归技术、分治、动态规划、贪心算法、图的遍历等技术,并且对np完全问题进行了基本但清楚的讨论。

算法设计技巧与分析-英文版 内容简介

  本书是国际著名算法专家李德财教授主编的系列丛书“lecture notes series on computing”中的一本。本书涵盖了绝大多数算法设计中的一般技术,在表达每一种技术时,阐述它的应用背景,注意用与其他技术比较的方法说明它的特征,并提供大量相应实际问题的例子。本书同时也强调了对每一种算法的详细的复杂性分析。   本书包含以下几部分   基本概念和算法导引   基于递归的技术   *先割技术   问题的复杂性   克服困难性   域指定问题的迭代改进   计算几何技术

算法设计技巧与分析-英文版 目录

part 1 basic concepts and introduction to algorithms
 chapter 1 basic concepts in algorithmic analysis
  1.1 introduction
  1.2 historical background
  1.3 binary search
  1.3.1 analysis of the binary search algorithm
  1.4 merging two sorted lists
  1.5 selection sort
  1.6 insertion sort
  1.7 bottomj.jp merge sorting
  1.7.1 analysis of bottom-up merge sorting
  1.8 time complexity
  1.9 space complexity
  1.10 optimal algorithms
  1.11 how to estimate the running time of an algorithm
  1.12 worst case and average case analysis
  1.13 amortized analysis
  1.14 input size and problem instance
  1.15 exercises
  1.16 bibliographic notes
 chapter 2 mathematical preliminaries
  2.1 sets, relations and functions
  2.2 proof methods
  2.3 logarithms
  2.4 floor and ceiling functions
  2.5 factorial and binomial coefficients
  2.6 the pigeonhole principle
  2.7 summations
  2.8 recurrence relations
  2.9 exercises
 chapter 3 data structures
  3.1 introduction
  3.2 linkedlists
  3.3 graphs
  3.4 trees
  3.5 rootedtyees
  3.5.1 tree traversals
  3.6 binary trees
  3.7 exercises
  3.8 bibliographic notes
 chapter 4 heaps and the disjoint sets data structures
  4.1 introduction
  4.2 heaps
  4.3 disjoint sets data structures
  4.4 exercises
  4.5 bibliographic notes
part 2 techniques based on recursion
 chapter 5 induction
  5.1 introduction
  5.2 two simple examples
  5.3 radix sort
  5.4 integer exponentiation
  5.5 evaluating polynomials (horner’s rule)
  5.6 generating permutations
  5.7 finding the majority element
  5.8 bibliographic notes
  5.9 exercises
 chapter 6 divide and conquer
  6.1 introduction
  6.2 binary search
  6.3 mergesort
  6.4 selection: finding the median and the kth smallestelement
  6.5 the divide and conquer paradigm
  6.6 quicksort
  6.7 multiplication of large integers
  6.8 matrix multiplication
  6.9 the closest pair problem
  6.10 exercises
  6.11 bibliographic notes
 chapter 7 dynamic programming
  7.1 introduction
  7.2 the longest common subsequence problem
  7.3 matrix chain multiplication
  7.4 the dynamic programming paradigm
  7.5 the all-pairs shortest path problem
  7.7 exercises
  7.6 the knapsack problem
  7.8 bibliographic notes
part 3 first-cut techniques
 chapter 8 the greedy approach
  8.1 introduction
  8.2 the shortest path problem
  8.3 minimum cost spanning trees (kruskal’s algorithm)
  8.4 minimum cost spanning trees (prim’s algorithm)
  8.5 file compression
  8.6 exercises
  8.7 bibliographic notes
 chapter 9 graph traversal
  9.1 introduction
  9.2 depth-first search
  9.3 applications of depth-first search
  9.4 breadth-first search
  9.5 applications of breadth-first search
  9.6 exercises
  9.7 bibliographic notes
part 4 complexity of problems
 chapter 10 np-complete problems
  10.1 introduction
  10.2 the class p
  10.3 the class np
  10.4 np-complete problems
  10.5 the class co-np
  10.6 the class npi
  10.7 the relationships between the four classes
  10.8 exercises
  10.9 bibliographic notes
 chapter 11 introduction to computational complexity
  11.1 introduction
  11.2 model of computation: the turing machine
  11.3 k-tape turing machines and time complexity
  11.4 off-line turing machines and space complexity
  11.5 tape compression and linear speed-up
  11.6 relationships between complexity classes
  11.7 reductions
  11.8 completeness
  11.9 the polynomial time hierarchy
  11.10exercises
  11.11 bibliographic notes
 chapter 12 lower bounds
  12.1 introduction
  12.2 trivial lower bounds
  12.3 the decision tree model
  12.4 the algebraic decision tree model
  12.5 linear time reductions
  12.6 exercises
  12.7 bibliographic notes
part 5 coping with hardness
 chapter 13 backtracking
  13.1 introduction
  13.2 the 3-coloring problem
  13.3 the 8-queens problem
  13.4 the general backtracking method
  13.5 branch and bound
  13.6 exercises
  13.7 bibliographic notes
 chapter 14 randomized algorithms
  14.1 introduction
  14.2 las vegas and monte carlo algorithms
  14.3 randomized quicksort
  14.4 randomized selection
  14.5 testing string equality
  14.6 pattern matching
  14.7 random sampling
  14.8 primality testing
  14.9 exercises
  14.10bibliographic notes
 chapter 15 approximation algorithms
  15.1 introduction
  15.2 basic definitions
  15.3 difference bounds
  15.4 relative performance bounds
  15.5 polynomial approximation schemes
  15.6 fully polynomial approximation schemes
  15.7 exercises
  15.8 bibliographic notes
part 6 iterative improvement for domain-specific problems
 chapter 16 network flow
  16.1 introduction
  16.2 preliminaries
  16.3 the ford-fulkerson method
  16.4 maximum capacity augmentation
  16.5 shortest path augmentation
  16.6 dinic’s algorithm
  16.7 the mpm algorithm
  16.8 exercises
  16.9 bibliographic notes
 chapter 17 matching
  17.1 introduction
  17.2 preliminaries
  17.3 the network flow method
  17.4 the hungarian tree method for bipartite graphs
  17.5 maximum matching in general graphs
  17.6 an o ( n2.5)algorithm for bipartite graphs
  17.7 exercises
  17.8 bibliographic notes
part 7 techniques in computational geometry
 chapter 18 geometric sweeping
  18.1 introduction
  18.2 geometric preliminaries
  18.3 computing the intersections of line segments
  18.4 the convex hull problem
  18.5 computing the diameter of a set of points
  18.6 exercises
  18.7 bibliographic notes
 chapter 19 voronoi diagrams
  19.1 introduction
  19.2 nearest-point voronoi diagram
  19.3 applications of the voronoi diagram
  19.4 farthest-point voronoi diagram
  19.5 applications of the farthest-point voronoi diagram
  19.6 exercises
  19.7 bibliographic notes
  bibliography
  index

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算法设计技巧与分析-英文版 作者简介

  M.H.Alsuwaiyel在沙特阿拉伯的King Fahd University of Petroleum&Minerals(KFUPM,皇家法哈德石油矿业大学)完成大学学业,在南加州(USC)大学获得计算机科学硕士和博士学位。作者曾任KFUPM的计算机科学系主任、工程与计算机学院院长。他在沙特阿拉伯有广泛的学术影响,是政府(包括内务部和国防部在内)的高级顾问。

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