An Introduction to the Analysis of Algorithms
An Introduction to the Analysis of Algorithms By Robert Sedgewick, Philippe Flajolet
Publisher: Addison-Wesley Professional 1995 | 512 Pages | ISBN: 020140009X | DJVU | 10 MB
This book is intended to be a thorough overview of the primary techniques used in the mathematical analysis of algorithms. The material covered draws from classical mathematical topics, including discrete mathematics, elementary real analysis, and combinatorics; as well as from classical computer science topics, including algorithms and data structures. The focus is on "average-case'' or "probabilistic'' analysis, though the basic mathematical tools required for "worst-case" or "complexity" analysis are covered, as well.
It is assumed that the reader has some familiarity with basic concepts in both computer science and real analysis. In a nutshell, the reader should be able to both write programs and prove theorems; otherwise, the book is intended to be self-contained. Ample references to preparatory material in the literature are also provided. A planned companion volume will cover more advanced techniques. Together, the books are intended to cover the main techniques and to provide access to the growing research literature on the analysis of algorithms.
The book is meant to be used as a textbook in a junior- or senior-level course on "Mathematical Analysis of Algorithms.'' It might also be useful in a course in discrete mathematics for computer scientists, since it covers basic techniques in discrete mathematics as well as combinatorics and basic properties of important discrete structures within a familiar context for computer science students. It is traditional to have somewhat broader coverage in such courses, but many instructors may find the approach here a useful way to engage students in a substantial portion of the material. The book also can be used to introduce students in mathematics and applied mathematics to principles from computer science related to algorithms and data structures.
Supplemented by papers from the literature, the book can serve as the basis for an introductory graduate course on the analysis of algorithms, or as a reference or basis for self-study by researchers in mathematics or computer science who want access to the literature in this field. It also might be of use to students and researchers in combinatorics and discrete mathematics, as a source of applications and techniques.
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An Introduction to the Analysis of Algorithms By Robert Sedgewick, Philippe Flajolet
Publisher: Addison-Wesley Professional 1995 | 512 Pages | ISBN: 020140009X | DJVU | 10 MB
This book is intended to be a thorough overview of the primary techniques used in the mathematical analysis of algorithms. The material covered draws from classical mathematical topics, including discrete mathematics, elementary real analysis, and combinatorics; as well as from classical computer science topics, including algorithms and data structures. The focus is on "average-case'' or "probabilistic'' analysis, though the basic mathematical tools required for "worst-case" or "complexity" analysis are covered, as well.
It is assumed that the reader has some familiarity with basic concepts in both computer science and real analysis. In a nutshell, the reader should be able to both write programs and prove theorems; otherwise, the book is intended to be self-contained. Ample references to preparatory material in the literature are also provided. A planned companion volume will cover more advanced techniques. Together, the books are intended to cover the main techniques and to provide access to the growing research literature on the analysis of algorithms.
The book is meant to be used as a textbook in a junior- or senior-level course on "Mathematical Analysis of Algorithms.'' It might also be useful in a course in discrete mathematics for computer scientists, since it covers basic techniques in discrete mathematics as well as combinatorics and basic properties of important discrete structures within a familiar context for computer science students. It is traditional to have somewhat broader coverage in such courses, but many instructors may find the approach here a useful way to engage students in a substantial portion of the material. The book also can be used to introduce students in mathematics and applied mathematics to principles from computer science related to algorithms and data structures.
Supplemented by papers from the literature, the book can serve as the basis for an introductory graduate course on the analysis of algorithms, or as a reference or basis for self-study by researchers in mathematics or computer science who want access to the literature in this field. It also might be of use to students and researchers in combinatorics and discrete mathematics, as a source of applications and techniques.
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