TY - GEN
T1 - Modeling Local Field Potentials with Regularized Matrix Data Clustering
AU - Gao, Xu
AU - Shen, Weining
AU - Hu, Jianhua
AU - Fortin, Norbert
AU - Ombao, Hernando
N1 - Funding Information:
ACKNOWLEDGEMENT Shen’s research is partially supported by the Simons Foundation (Award 512620) and the National Science Foundation (NSF DMS 1509023).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/5/16
Y1 - 2019/5/16
N2 - In this paper, we propose a novel regularized mixture model for clustering matrix-valued image data. The new framework introduces a sparsity structure (e.g., low rank, spatial sparsity) and separable covariance structure motivated by scientific interpretability. We formulate the problem as a fi-nite mixture model of matrix-normal distributions with regularization terms, and then develop an Expectation-Maximization-type of algorithm for efficient computation. Simulation results and analysis on brain signals show the excellent performance of the proposed method in terms of a better prediction accuracy than the competitors and the scientific interpretability of the solution.
AB - In this paper, we propose a novel regularized mixture model for clustering matrix-valued image data. The new framework introduces a sparsity structure (e.g., low rank, spatial sparsity) and separable covariance structure motivated by scientific interpretability. We formulate the problem as a fi-nite mixture model of matrix-normal distributions with regularization terms, and then develop an Expectation-Maximization-type of algorithm for efficient computation. Simulation results and analysis on brain signals show the excellent performance of the proposed method in terms of a better prediction accuracy than the competitors and the scientific interpretability of the solution.
UR - http://www.scopus.com/inward/record.url?scp=85066735452&partnerID=8YFLogxK
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U2 - 10.1109/NER.2019.8717132
DO - 10.1109/NER.2019.8717132
M3 - Conference contribution
AN - SCOPUS:85066735452
T3 - International IEEE/EMBS Conference on Neural Engineering, NER
SP - 597
EP - 602
BT - 9th International IEEE EMBS Conference on Neural Engineering, NER 2019
PB - IEEE Computer Society
T2 - 9th International IEEE EMBS Conference on Neural Engineering, NER 2019
Y2 - 20 March 2019 through 23 March 2019
ER -