A wavelet based algorithm for pattern analysis

Chris Bowman, Thierry Passot, Michel Assenheimer, Alan C. Newell

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Patterns with a local roll structure arise in many diverse physical systems which have little in common at the microscopic level. In this paper we construct an algorithm based on the wavelet transform that can be used as a diagnostic tool to extract from such patterns macroscopic information like the local director field, the local amplitude away from defects, and slowly varying fields, such as mean drift, which may be soft modes of pattern. It allows a precise detection of phase grain boundaries and point defects. Several tests are conducted on numerically generated signals to demonstrate the applicability and precision of the algorithm. Finally, the algorithm is applied to actual experimental convection patterns, allowing us to draw several conclusions about the nature of the wave director field in such patterns.

Original languageEnglish (US)
Pages (from-to)250-282
Number of pages33
JournalPhysica D: Nonlinear Phenomena
Volume119
Issue number3-4
DOIs
StatePublished - Jan 1 1998
Externally publishedYes

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • Condensed Matter Physics
  • Applied Mathematics

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