Markov Chain Monte Carlo Inference of Parametric Dictionaries for Sparse Bayesian Approximations

@article{Chaspari2016MarkovCM,
  title={Markov Chain Monte Carlo Inference of Parametric Dictionaries for Sparse Bayesian Approximations},
  author={Theodora Chaspari and Andreas Tsiartas and Panagiotis Tsilifis and Shrikanth Narayanan},
  journal={IEEE Transactions on Signal Processing},
  year={2016},
  volume={64},
  pages={3077-3092}
}
Parametric dictionaries can increase the ability of sparse representations to meaningfully capture and interpret the underlying signal information, such as encountered in biomedical problems. Given a mapping function from the atom parameter space to the actual atoms, we propose a sparse Bayesian framework for learning the atom parameters, because of its… CONTINUE READING