Average Case Analysis of Algorithms on Sequences (eBook)

WOJCIECH SZPANKOWSKI, PhD, is Professor of Computer Science at Purdue University and has held visiting research positions at the Technical University of Gdansk, McGill University, INRIA, the Technical University of Vienna, University of Witwatersrand, Hewlett-Packard Laboratories, and Stanford University. He is the author of over 100 scientific publications in the areas of analysis of algorithms, information theory, performance evaluation of computer networks, stability of distributed systems, and queueing theory.

Foreword.

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.

"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)