算法：自上而下的方法 Algorithms: A Top-down Approach
基本信息
Format Hardback | 612 pages
Dimensions 169.93 x 244.09 x 33.27mm | 1,165.73g
Publication date 03 Feb 2023
Publisher World Scientific Publishing Co Pte Ltd
ISBN10 9811263833
ISBN13 9789811263835
页面参数仅供参考，具体以实物为准
书籍简介
这本综合汇编提供了一个严格的框架，以应对设计正确和高效算法的艰巨挑战。它对算法的设计、分析、优化和验证给出了统一的方法。该卷还提供了理解算法及其相关数据结构的基本工具。
这本有用的参考书描述了一种简化算法正确性证明任务的思维方式。通过对正确性的证明，揭示了算法的微妙之处，这是典型的描述所无法做到的。算法分析是用仔细的定义来介绍的，这些定义使分析在数学上很严谨。
This comprehensive compendium provides a rigorous framework to tackle the daunting challenges of designing correct and efficient algorithms. It gives a uniform approach to the design, analysis, optimization, and verification of algorithms. The volume also provides essential tools to understand algorithms and their associated data structures.
This useful reference text describes a way of thinking that eases the task of proving algorithm correctness. Working through a proof of correctness reveals an algorithm's subtleties in a way that a typical description does not. Algorithm analysis is presented using careful definitions that make the analyses mathematically rigorous.
作者简介
By (author): Rodney R Howell (Kansas State University, USA)
罗德尼-豪威尔1984年在威奇托州立大学获得计算机科学学士学位，1988年在德克萨斯大学奥斯汀分校获得计算机科学博士学位。1988年8月，他加入了堪萨斯州立大学的计算和信息科学系（现在的计算机科学），担任助理教授。1994年，他被提升为副教授级别。自2014年以来，他一直担任该系的本科生课程主任。
Rodney Howell received a bachelor’s degree in computer science from Wichita State University in 1984 and a doctorate degree in computer science from The University of Texas at Austin in 1988. In August 1988, he joined the department of computing and information sciences (now computer science) at Kansas State University as an assistant professor. In 1994, he was promoted to the rank of associate professor. Since 2014, he has served as the department’s undergraduate programs director.
目录
Fundamentals:
Introduction
Proving Algorithm Correctness
Analyzing Algorithms
Data Structures:
Basic Techniques for Data Structures
Priority Queues
Storage/Retrieval I: Ordered Keys
Storage/Retrieval II: Unordered Keys
Disjoint Sets
Graphs
Algorithm Design Techniques:
Divide and Conquer
Optimization I: Greedy Algorithms
Optimization II: Dynamic Programming
Common Reduction Targets:
Depth-First Search
Network Flow and Matching
* The Fast Fourier Transform
Intractable Problems:
NP-Completeness
Approximation Algorithms
