By Topic

Feature Waveform Extraction Based on Shape- and Position-Adapted Nonparametric Waveform Atoms

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Qingfeng Meng ; Key Lab. of Educ. Minist. for Modern Design & Rotor-Bearing Syst., Xi'an Jiaotong Univ., Xi'an, China ; Jingyuan Sun ; Hong Fan ; Licheng Jiao

In this paper, we introduce a novel method for extracting feature waveforms from signal, which is based on nonparametric waveform atoms. Using a template signal that contains a prior information, a set of basis functions is obtained firstly by means of a uniform filter bank and then a nonparametric atom that is described by a series of discrete data are constructed. The filter bank makes the waveform atom shape-adapted and a delay expansion of the subbands of the filter bank makes the atom position-adapted. Using the constructed atoms, an algorithm for extracting waveforms from signal can be developed based on singular value decomposition (SVD) and matching pursuit (MP). Examples from the simulation analysis and the damping experiment on a rotor-bearing system have confirmed the proposed method. It is shown that the constructed waveform atom can adapt itself to the variations of the feature waveform in the observed signal.

Published in:

Computer Science and Information Engineering, 2009 WRI World Congress on  (Volume:6 )

Date of Conference:

March 31 2009-April 2 2009