Description
Book SynopsisA timely book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications, most notably in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms, combining both analytical and probabilistic tools in a single volume.
Trade Review"Surveying the major techniques of average case analysis, this graduate textbook presents both analytical methods used for well-structured algorithms and probabilistic methods used for more structurally complex algorithms." (SciTech Book News, Vol. 25, No. 3, September 2001)
"...contains a comprehensive treatment on probabilistic, combinatorial, and analytical techniques and methods...treatment is clear, rigorous, self-contained, with many examples and exercises." (Zentralblatt MATH Vol. 968, 2001/18)
"This well-organized book...is certainly useful...It is a valuable source for a deeper and more precise understanding of the behaviors of algorithms on sequences." (Mathematical Reviews, 2002f)
Table of ContentsForeword.
Preface.
Acknowledgments.
PROBLEMS ON WORDS.
Data Structures and Algorithms on Words.
Probabilistic and Analytical Models.
PROBABILISTIC AND COMBINATORIAL TECHNIQUES.
Inclusion-Exclusion Principle.
The First and Second Moment Methods.
Subadditive Ergodic Theorem and Large Deviations.
Elements of Information Theory.
ANALYTIC TECHNIQUES.
Generating Functions.
Complex Asymptotic Methods.
Mellin Transform and Its Applications.
Analytic Poissonization and Depoissonization.
Bibliography.
Index.
