A quantitative study of the efficiency of computer methods requires an in-depth understanding of both mathematics and computer science. This monograph, derived from an advanced computer science course at Stanford University, builds on the fundamentals of combinatorial analysis and complex variable t
Mathematics for the analysis of algorithms
✍ Scribed by Daniel H Greene
- Publisher
- Birkhauser
- Year
- 1981
- Tongue
- English
- Leaves
- 110
- Series
- Progress in computer science
- Category
- Library
No coin nor oath required. For personal study only.
✦ Synopsis
A quantitative study of the efficiency of computer methods requires an in-depth understanding of both mathematics and computer science. This monograph, derived from an advanced computer science course at Stanford University, builds on the fundamentals of combinatorial analysis and complex variable theory to present many of the major paradigms used in the precise analysis of algorithms, emphasizing the more difficult notions. The authors cover recurrence relations, operator methods, and asymptotic analysis in a format that is terse enough for easy reference yet detailed enough for those with little background. Approximately half the book is devoted to original problems and solutions from examinations given at Stanford.
✦ Subjects
Информатика и вычислительная техника;Теория алгоритмов;
📜 SIMILAR VOLUMES
This monograph collects some fundamental mathematical techniques that are required for the analysis of algorithms. It builds on the fundamentals of combinatorial analysis and complex variable theory to present many of the major paradigms used in the precise analysis of algorithms, emphasizing the mo
<p><P>A quantitative study of the efficiency of computer methods requires an in-depth understanding of both mathematics and computer science. This monograph, derived from an advanced computer science course at Stanford University, builds on the fundamentals of combinatorial analysis and complex vari
A quantitative study of the efficiency of computer methods requires an in-depth understanding of both mathematics and computer science. This monograph, derived from an advanced computer science course at Stanford University, builds on the fundamentals of combinatorial analysis and complex variable t
This book is a gem of problem sets AND solutions, in the field of algorithms. The problems were from actual examinations given at Stanford in various computer science classes. About half the book is good descriptive text about the ideas that the problems probe. Certainly, well written, as befits Knu