Prof. Michael Elad has been selected for the 2018 SPS (Signal
Processing Society) Technical Achievement Award for contributions to sparsity-based
signal processing.
Michael Elad together with two past Ph.D. students, Tomer Peleg and Ron
Rubinstein, have been selected for the 2018 IEEE Signal Processing Best Paper
Award for our paper titled "Analysis K-SVD: A Dictionary-Learning Algorithm for
the Analysis Sparse Model".
Michael Elad together with Michal Aharon, and Alfred Bruckstein, have been
selected for the 2018 IEEE SPS Sustained Impact Paper Award for the below noted
paper: "K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse
Representation" IEEE Transactions on Signal Processing, Volume 54, Number 11,
November 2006.