2013
Coursera / Princeton University
Robert Sedgewick
~13 h
English
This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. Part I covers generating functions and real asymptotics and then introduces the symbolic method in the context of applications in the analysis of algorithms and basic structures such as permutations, trees, strings, words, and mappings.
Analytic Combinatorics aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the scientific analysis of algorithms in computer science and for the study of scientific models in many other disciplines, including probability theory, statistical physics, computational biology and information theory. Part I of this course covers recurrence relations, generating functions, asymptotics, and fundamental structures such as trees, permutations, strings, tries, words, and mappings, in the context of applications to the analysis of algorithms.
Lecture 1 Analysis of Algorithms
Lecture 2 Recurrences
Lecture 3 Solving recurrences with GFs
Lecture 4 Asymptotics
Lecture 5 The symbolic method
Lecture 6 Trees
Lecture 7 Permutations
Lecture 8 Strings and Tries
Lecture 9 Words and Mappings
www.coursera.org

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