Fourier Analysis on Groups, Random Walks and Markov Chains

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In Chap. 1 it is explained that if p is a probability on a finite group G the group matrix XG(p) is a transition matrix for a random walk on G. If f is an arbitrary function on G the process of transforming XG(f) into a block diagonal matrix is equivalent to the obtaining the Fourier transform of f. This chapter explains the connections with harmonic analysis and the group matrix. Most of the discussion is on probability theory and random walks. The fusion of characters discussed in Chap. 4 becomes relevant, and also the idea of fission of characters is introduced, especially those fissions which preserve diaonalizability of the corresponding group matrix. As an example of how the group matrix and group determinant can be used as tools, their application to random walks which become uniform after a finite number of steps is examined.

Original languageEnglish (US)
Title of host publicationLecture Notes in Mathematics
PublisherSpringer Verlag
Pages231-270
Number of pages40
DOIs
StatePublished - Jan 1 2019

Publication series

NameLecture Notes in Mathematics
Volume2233
ISSN (Print)0075-8434
ISSN (Electronic)1617-9692

All Science Journal Classification (ASJC) codes

  • Algebra and Number Theory

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  • Cite this

    Johnson, K. W. (2019). Fourier Analysis on Groups, Random Walks and Markov Chains. In Lecture Notes in Mathematics (pp. 231-270). (Lecture Notes in Mathematics; Vol. 2233). Springer Verlag. https://doi.org/10.1007/978-3-030-28300-1_7