Maximum Likelihood Estimation From Sign Measurements With Sensing Matrix Perturbation

@article{Zhu2014MaximumLE,
  title={Maximum Likelihood Estimation From Sign Measurements With Sensing Matrix Perturbation},
  author={Jiang Zhu and Xiaohan Wang and Yuantao Gu},
  journal={IEEE Transactions on Signal Processing},
  year={2014},
  volume={62},
  pages={3741-3753}
}
The problem of estimating an unknown deterministic parameter vector from sign measurements with a perturbed sensing matrix is studied in this paper. We analyze the best achievable mean-square error (MSE) performance by exploring the corresponding Cramér-Rao lower bound (CRLB). To estimate the parameter, the maximum likelihood (ML) estimator is utilized and its consistency is proved. We show that, compared with the perturbed-free setting, the perturbation on the sensing matrix exacerbates the… CONTINUE READING