TY - GEN
T1 - Minimax game-theoretic approach to multiscale H-infinity optimal filtering
AU - Anwar, Hamza
AU - Zhu, Quanyan
N1 - Funding Information:
This work is partially supported by the grants EFMA-1441140 and SES- 1541164 from National Science Foundation.
Funding Information:
This work is partially supported by the grants EFMA-1441140 and SES-1541164 from National Science Foundation.
Publisher Copyright:
© 2017 IEEE.
PY - 2018/3/7
Y1 - 2018/3/7
N2 - 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).
AB - 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).
KW - Multi-resolution analysis
KW - dynamic games
KW - hierarchical systems
KW - minimax techniques
KW - state estimation
UR - http://www.scopus.com/inward/record.url?scp=85048050998&partnerID=8YFLogxK
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U2 - 10.1109/GlobalSIP.2017.8309081
DO - 10.1109/GlobalSIP.2017.8309081
M3 - Conference contribution
AN - SCOPUS:85048050998
T3 - 2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings
SP - 853
EP - 857
BT - 2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017
Y2 - 14 November 2017 through 16 November 2017
ER -