算法技术手册(影印版)(Algorithms in a Nutshell)

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基本信息·出版社:东南大学出版社

·页码:343 页

·出版日期:2009年

·ISBN:7564116323/9787564116323

·条形码:9787564116323

·包装版本:1版

·装帧:平装

·开本:16

·正文语种:英语

·外文书名:Algorithms in a Nutshell

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内容简介创造稳定的软件需要有效的算法,但是程序设计者们很少能在问题出现之前就想到。《算法技术手册(影印版)》描述了现有的可以解决多种问题的算法,并且能够帮助你根据需求选择并实现正确的算法——只需要一定的数学知识即可理解并分析算法执行。相对于理论来说,本书更注重实际运用,书中提供了多种程序语言中可用的有效代码解决方案,可轻而易举地适合一个特定的项目。有了这本书,你可以:

解决特定编码问题或改进现有解决方案的执行;

迅速确定与需要解决的问题相关的算法,并判定为什么这样的算法是正确的;

探索C、C++、Java、Ruby中的算法解决方案,伴有实现诀窍;

了解一个算法预期的执行情况及最佳的执行条件;

发现不同算法中相似设计产生的冲突;

学习先进的数据结构以改进算法效率。

有了《算法技术手册》,你可以学习如何改进算法的性能,这是软件应用成功的关键。

作者简介George T.Heineman,Gary Pollice和Stanley Selkow均为 Woree ste r PolYteChniC In stitute(伍斯特理工学院)计算机科学系的教授。George是《Component—B ased Software Engineering:Putting the Pieces Together》(Addison—Wesley(的合编者,Gary则是《Head First Object-Oriented Analysis and Design》(O'Reilly)的合著者。

媒体推荐“作者汲取了大量鲜为人知的文献资料,这本不可或缺的指南巩固了理论与实际操作的完美平衡。通过它来理解算法变得更加轻松容易。”

——Matthew Russell.高级技术总监,Digital Reasoning System;《Doj0:The Definitive Guide》的作者(O'Reilly)

编辑推荐《算法技术手册(影印版)》由东南大学出版社出版。

目录

Part 1

1. Algorithms Matter

Understand the Problem

Experiment if Necessary

Algorithms to the Rescue

Side Story

The Moral of the Story

References

2. The Mathematics of Algorithms

Size of a Problem Instance

Rate of Growth of Functions

Analysis in the Best, Average, and Worst Cases.

Performance Families

Mix of Operations

Benchmark Operatxons

One Final Point

References

3. Patterns and Domains

Patterns: A Communication Language

Algorithm Pattern Format

Pseudocode Pattern Format

Design Format

Empirical Evaluation Format

Domains and Algorithms

Floating-Point Computations

Manual Memory Allocation

Choosing a Programming Language

References

Part 2

4. Sorting Algorithms

Overview

Insertion Sort

Median Sort

Quicksort

Selection Sort

Heap Sort

Counting Sort

Bucket Sort

Criteria for Choosing a Sorting Algorithm

References

5. Searching

Overview

Sequential Search

Binary Search

Hash-based Search

Binary Tree Search

6. GraphAIgorithms

Overview

Depth-First Search

Breadth-First Search

Single-Source Shortest Path

All Pairs Shortest Path

Minimum Spanning Tree Algorithms

References

7. Path Finding in AI

Overview

Depth-First Search

Breadth-First Search

A'Search

Comparison

Minimax

NegMax

AlphaBeta

References

8. Network Flow Algorithms

Overview

Maximum Flow

Bipartite Matching

Reflections on Augmenting Paths

Minimum Cost Flow

Transshipment

Transportation

Assignment

Linear Programming

References

9. Computational Geometry

Overview

Convex Hull Scan

LineSweep

Nearest Neighbor Queries

Range Queries

References

Part 3

10. When All Else Fails

Variations on a Theme

Approximation Algorithms

Offline Algorithms

Parallel Algorithms

Randomized Algorithms

Algorithms That Can Be Wrong, but with Diminishing Probability References

11. Epilogue

Overview

Principle: Know Your Data

Principle: Decompose the Problem into Smaller Problems

Principle: Choose the Right Data Structure

Principle: Add Storage to Increase Performance

Principle: If No Solution Is Evident, Construct a Search

Principle: If No Solution Is Evident, Reduce Your Problem to

Another Problem That Has a Solution

Principle: Writing Algorithms Is Hard——Testing Algorithms Is Harder

Part 4

Appendix: Benchmarking

Index

……[看更多目录]

文摘插图:

算法技术手册(影印版)(Algorithms in a Nutshell)

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