Adaptive splitting technique for Gaussian mixture models to solve Kolmogorov Equation

Kumar Vishwajeet, Puneet Singla

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

7 Scopus citations

Abstract

The accuracy and the computational complexity of a Gaussian mixture model depends upon the number of components. In a stochastic dynamical system, the number of these components must change over time to account for the change in the uncertainty over time. A new splitting technique is provided based on the minimization of Fokker Planck Kolmogorov Equation. The effect of the splitting on the other components is also discussed in the work.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5186-5191
Number of pages6
ISBN (Print)9781479932726
DOIs
StatePublished - Jan 1 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2014 American Control Conference, ACC 2014
CountryUnited States
CityPortland, OR
Period6/4/146/6/14

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Vishwajeet, K., & Singla, P. (2014). Adaptive splitting technique for Gaussian mixture models to solve Kolmogorov Equation. In 2014 American Control Conference, ACC 2014 (pp. 5186-5191). [6859240] (Proceedings of the American Control Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2014.6859240