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      • Department of Electrical and Electronics Engineering
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      Logarithmic regret bound over diffusion based distributed estimation

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      Author
      Sayın, Muhammed O.
      Vanlı, Nuri Denizcan
      Kozat, Süleyman Serdar
      Date
      2014
      Source Title
      Proceedings of the 39th International Conference on Acoustics, Speech and Signal Processing, IEEE 2014
      Print ISSN
      1520-6149
      Publisher
      IEEE
      Pages
      8287 - 8291
      Language
      English
      Type
      Conference Paper
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      Abstract
      We provide a logarithmic upper-bound on the regret function of the diffusion implementation for the distributed estimation. For certain learning rates, the bound shows guaranteed performance convergence of the distributed least mean square (DLMS) algorithms to the performance of the best estimation generated with hindsight of spatial and temporal data. We use a new cost definition for distributed estimation based on the widely-used statistical performance measures and the corresponding global regret function. Then, for certain learning rates, we provide an upper-bound on the global regret function without any statistical assumptions.
      Keywords
      Estimation
      Signal processing
      Cost definition
      Distributed
      Distributed estimation
      Guaranteed performance
      Learning rates
      Least mean squares
      Regret
      Statistical performance measures
      Diffusion
      Permalink
      http://hdl.handle.net/11693/27374
      Published Version (Please cite this version)
      https://doi.org/10.1109/ICASSP.2014.6855217
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      • Department of Electrical and Electronics Engineering 3524
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