Fusing heterogeneous data for detection under non-stationary dependence

@article{He2012FusingHD,
  title={Fusing heterogeneous data for detection under non-stationary dependence},
  author={Hao He and Arun Subramanian and Pramod K. Varshney and Thyagaraju R. Damarla},
  journal={2012 15th International Conference on Information Fusion},
  year={2012},
  pages={1792-1799}
}
In this paper, we consider the problem of detection for dependent, non-stationary signals where the non-stationarity is encoded in the dependence structure. We employ copula theory, which allows for a general parametric characterization of the joint distribution of sensor observations and, hence, allows for a more general description of inter-sensor dependence. We design a copula-based detector using the Neyman-Pearson framework. Our approach involves a sample-wise copula selection scheme… CONTINUE READING

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