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Virginia Tech

Signal decomposition for nonstationary processes

Abstract

dc:description.abstract

The main purpose of this dissertation is to explore and develop better signal modeling (decomposition) methods for nonstationary and/or nonlinear dynamic processes. Localization is the main focus. The characteristics of a nonstationary or nonlinear signal are decomposed onto a set of basis functions, either in the phase space spanned by time-frequency coordinates as Gabor proposed, or in the phase space spanned by a set of derivatives of different degree as defined in physics. To deal with time-varying signals, a Multiresolution Parametric Spectral Estimator (MPSE) is proposed together with its theory, techniques and applications. The resolution study provides the characteristics of windowed Fourier transforms, wavelet transforms, fixed resolution parametric spectral estimators, and the newly developed MPSE. Both the theoretical and the experimental results show that, of the above techniques, MPSE is the best in resolution. Furthermore, with proper a priori knowledge, MPSE can yield better resolution than the lower bound defined by the Heisenberg uncertainty principle. The application examples demonstrate the great potential of the MPSE method for tracking and analyzing time-varying processes. To deal with the time-varying characteristics caused by linearization of nonlinear processes, the Radial Basis Function Network (RBFN) is proposed for modeling nonlinear processes from a 'local' to a 'global' level. An equal distance sample rule is proposed for constructing the RBEN. Experiments indicate that the RBFN is a promising method for modeling deterministic chaos as well as stochastic processes, be it linear or nonlinear. The 'local' to 'global' approach of the RBEN also provides great potential for structure adaptation and knowledge accumulation.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Electrical Engineering
Department dc:contributor.department
Electrical Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
1995

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Xie, Min
Chair dc:contributor.committeechair
  • Beex, Aloysius A.
Committee members dc:contributor.committeemember
  • Jacobs, Ira
  • Bay, John S.
  • Baumann, William T.
  • Pribram, K.H.

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
etd-06062008-162359
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/38185

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Xie, Min. Signal decomposition for nonstationary processes. doctoral thesis, Virginia Tech, 1995. http://hdl.handle.net/10919/38185