Fast Waveform Pattern Matching With Significant-Point Frames

The basic technique of scale-space filtering has been modified to render it suitable for detecting instances of short-duration "patterns" in one-dimensional waveform data. Scale-space filtering involves convolving a signal with a parametric kernel, such as the Gaussian function. The contour plot and interval tree record migrations and disappearances of the level-crossings of linear differential operators across multiple convolutions. These structures can be viewed as compressed, hierarchical representations of the signal, and have served as bases of successful systems for pattern matching The interval tree proves unsuitable, however, for representing signals of short duration, for which migrations of the level-crossings across data-interval boundaries cause loss of contour-plot information.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Mayse, William Clark

Contributors dc:contributor

• Ray, S.R.,

• Computer Science

Identifier

(UMI)AAI9305617

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/72071