Approximate Message Passing

Bayesian methods for sparse signal recovery with automatic hyperparameter estimation

Approximate Message Passing with Built-in Parameter Estimation

Under the Bayesian framework, the signal x follows a sparsity-promoting distribution. The distribution parameters are treated as unknown variables and jointly recovered with the signal via Approximate Message Passing (Huang et al., 2022).

The proposed AMP-PE framework.

References

2022

TSP

Approximate Message Passing With Parameter Estimation for Heavily Quantized Measurements

Shuai Huang, Deqiang Qiu, and Trac D. Tran

IEEE Transactions on Signal Processing, 2022

Bib HTML

@article{AMP_PE_1bit,
  author = {Huang, Shuai and Qiu, Deqiang and Tran, Trac D.},
  journal = {IEEE Transactions on Signal Processing},
  title = {Approximate Message Passing With Parameter Estimation for Heavily Quantized Measurements},
  year = {2022},
  volume = {70},
  number = {},
  pages = {2062-2077}
}