Information Estimation from Partially Missed Data

@article{Torokhti2007InformationEF,
  title={Information Estimation from Partially Missed Data},
  author={A. Torokhti and P. Howlett and C. Pearce},
  journal={2007 IEEE International Symposium on Information Theory},
  year={2007},
  pages={2011-2015}
}
We provide a new technique for random signal estimation under the constraints that the data is corrupted by random noise and moreover, some data may be missed. We utilize nonlinear filters defined by multi-linear operators of degree r, the choice of which allows a trade-off between the accuracy of the optimal filter and the complexity of the corresponding calculations. A rigorous error analysis is presented. 

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