Minimax game-theoretic approach to multiscale H-infinity optimal filtering

Hamza Anwar, Quanyan Zhu

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

Abstract

Sensing in complex systems requires large-scale information exchange and on-the-go communications over heterogeneous networks and integrated processing platforms. Many networked cyber-physical systems exhibit hierarchical infrastructures of information flows, which naturally leads to a multi-level tree-like information structure in which each level corresponds to a particular scale of representation. This work focuses on the multiscale fusion of data collected at multiple levels of the system. We propose a multiscale state-space model to represent multi-resolution data over the hierarchical information system and formulate a multi-stage dynamic zero-sum game to design a multi-scale H robust filter. We present numerical experiments for one and two-dimensional signals and provide a comparative analysis of the minimax filter with the standard Kalman filter to show the improvement in signal-to-noise ratio (SNR).

Original languageEnglish (US)
Title of host publication2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages853-857
Number of pages5
Volume2018-January
ISBN (Electronic)9781509059904
DOIs
StatePublished - Mar 7 2018
Event5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Montreal, Canada
Duration: Nov 14 2017Nov 16 2017

Other

Other5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017
CountryCanada
CityMontreal
Period11/14/1711/16/17

Fingerprint

Heterogeneous networks
Kalman filters
Large scale systems
Signal to noise ratio
Ion exchange
Information systems
Fusion reactions
Communication
Processing
Experiments
Cyber Physical System

Keywords

  • dynamic games
  • hierarchical systems
  • minimax techniques
  • Multi-resolution analysis
  • state estimation

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

Cite this

Anwar, H., & Zhu, Q. (2018). Minimax game-theoretic approach to multiscale H-infinity optimal filtering. In 2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings (Vol. 2018-January, pp. 853-857). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2017.8309081

Minimax game-theoretic approach to multiscale H-infinity optimal filtering. / Anwar, Hamza; Zhu, Quanyan.

2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 853-857.

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

Anwar, H & Zhu, Q 2018, Minimax game-theoretic approach to multiscale H-infinity optimal filtering. in 2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 853-857, 5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017, Montreal, Canada, 11/14/17. https://doi.org/10.1109/GlobalSIP.2017.8309081
Anwar H, Zhu Q. Minimax game-theoretic approach to multiscale H-infinity optimal filtering. In 2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 853-857 https://doi.org/10.1109/GlobalSIP.2017.8309081
Anwar, Hamza ; Zhu, Quanyan. / Minimax game-theoretic approach to multiscale H-infinity optimal filtering. 2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 853-857
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