Effective EEG Connectivity by Sparse Vector Autoregressive Model
Pages 37 - 45
Abstract
This paper introduces a time domain approach based on Granger causality for estimating directional flow between multivariate time series. It is formulated under the framework of vector autoregressive model. Sparse regression is used to find the solution to the VAR model and validation of the results are carried out with the help of simulations. We also demonstrate the application of this method on actual EEG dataset.
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Index Terms
- Effective EEG Connectivity by Sparse Vector Autoregressive Model
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Published In
January 2020
399 pages
ISBN:9781450377386
DOI:10.1145/3371158
- General Chairs:
- Vasudeva Varma,
- Subbarao Kambhampati,
- Program Chairs:
- Arnab Bhattacharya,
- Sriraam Natarajan,
- Publications Chair:
- Rishiraj Saha Roy
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Published: 15 January 2020
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CoDS COMAD 2020 Paper Acceptance Rate 78 of 275 submissions, 28%;
Overall Acceptance Rate 197 of 680 submissions, 29%
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