New switched filtering method for recurrent neural networks

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

Abstract

In this paper, we propose a new robust filtering method for switched neural networks via input/output-to-state stability (IOSS) approach. This robust filtering method guarantees that the filtering error system is asymptotically stable and input/output-to-state stable for the external disturbance. The unknown gain matrix of the proposed filter can be obtained by solving a set of linear matrix inequalities (LMIs), which can be easily facilitated by using some standard numerical packages.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011
Pages71-74
Number of pages4
Volume1
DOIs
Publication statusPublished - 2011 Sep 28
Externally publishedYes
Event2011 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011 - Bali, Indonesia
Duration: 2011 Aug 42011 Aug 7

Other

Other2011 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011
CountryIndonesia
CityBali
Period11/8/411/8/7

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Keywords

  • input/output-to-state stability
  • robust filtering
  • switched neural networks

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computational Theory and Mathematics

Cite this

Ahn, C. K. (2011). New switched filtering method for recurrent neural networks. In Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011 (Vol. 1, pp. 71-74). [6007842] https://doi.org/10.1109/URKE.2011.6007842