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Author: SigProcessing

README.md

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 # Learning Mixtures of Separable Dictionaries for Tensor Data: Codebase for Numerical Experiments
 
 ## Table of Contents
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 **Paper Citation:** M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, "Learning mixtures of separable dictionaries for tensor data: Analysis and algorithms," IEEE Trans. Signal Processing, vol. 68, pp. 33-48, 2020; doi: [10.1109/TSP.2019.2952046](https://doi.org/10.1109/TSP.2019.2952046).
 
-**Codebase Citation:** J. Shenouda, M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, "Codebase---Learning mixtures of separable dictionaries for tensor data: Analysis and algorithms," GitHub Repository, 2020.
+**Codebase Citation:** J. Shenouda, M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, "Codebase---Learning mixtures of separable dictionaries for tensor data: Analysis and algorithms," GitHub Repository, 2020; doi: [10.5281/zenodo.3901853](https://doi.org/10.5281/zenodo.3901853).
 
 ## Computing Environment
 All of our computational experiments were done using MATLAB R2019a. All the experiments were carried out on a Linux high-performance computing (HPC) cluster provided by the Rutgers Office of Advanced Research in Computing; specifically, all of the experiments were run on: