Nonparametric density estimation based independent component analysis via particle swarm optimization

D. J. Krusienski, W. K. Jenkins

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

This paper investigates the application of a modified particle swarm optimization technique to nonparametric density estimation based independent component analysis (ICA). Nonparametric ICA has the advantage over traditional ICA techniques in that its performance is not dependent upon prior assumptions about the source distributions. Particle swarm optimization (PSO) is similar to the genetic algorithm in that it utilizes a population based search suitable for optimizing multimodal error surfaces where gradient-based algorithms tend to fail, such as those generated by nonlinear entropy maximization schemes used in ICA algorithms.

Original languageEnglish (US)
Title of host publication2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions
PublisherInstitute of Electrical and Electronics Engineers Inc.
PagesIV357-IV360
ISBN (Print)0780388747, 9780780388741
DOIs
StatePublished - Jan 1 2005
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: Mar 18 2005Mar 23 2005

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
VolumeIV
ISSN (Print)1520-6149

Other

Other2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
CountryUnited States
CityPhiladelphia, PA
Period3/18/053/23/05

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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    Krusienski, D. J., & Jenkins, W. K. (2005). Nonparametric density estimation based independent component analysis via particle swarm optimization. In 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions (pp. IV357-IV360). [1416019] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. IV). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2005.1416019