A Stimuli-Relevant Directed Dependency Index for Time Series

Payam Shahsavari Baboukani; Sergios Theodoridis; Jan Østergaard

doi:10.1109/ICASSP43922.2022.9747254

A Stimuli-Relevant Directed Dependency Index for Time Series

Payam Shahsavari Baboukani, Sergios Theodoridis, Jan Østergaard

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

Abstract

Transfer entropy can to a certain degree assess the direction in addition to the strength of the couplings within dynamic time series. The greater the transfer entropy, the greater the strength of the dependency between time series. In this work, we are interested in quantifying the effect that a given time series (e.g., an external stimuli) has upon the coupling strength between other time series. Towards that end, we define a directed dependency index based on the difference of two causally conditioned transfer entropies. We then provide a lower bound for the dependency index, and demonstrate on synthetic data that this lower bound can be efficiently computed.

Original language	English
Title of host publication	2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
Number of pages	5
Publisher	IEEE Signal Processing Society
Publication date	2022
Pages	5812-5816
ISBN (Electronic)	9781665405409
DOIs	https://doi.org/10.1109/ICASSP43922.2022.9747254
Publication status	Published - 2022
Event	47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Virtual, Online, Singapore Duration: 23 May 2022 → 27 May 2022

Conference

Conference	47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
Country/Territory	Singapore
City	Virtual, Online
Period	23/05/2022 → 27/05/2022
Sponsor	Chinese and Oriental Languages Information Processing Society (COLPIS), Singapore Exhibition and Convention Bureau, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), The Institute of Electrical and Electronics Engineers Signal Processing Society

Series	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2022-May
ISSN	1520-6149

Bibliographical note

Publisher Copyright:
© 2022 IEEE

Keywords

directed dependecy
intrinsic mutual information
mutual information
Transfer entropy

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10.1109/ICASSP43922.2022.9747254

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Baboukani, Payam Shahsavari ; Theodoridis, Sergios ; Østergaard, Jan. / A Stimuli-Relevant Directed Dependency Index for Time Series. 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings. IEEE Signal Processing Society, 2022. pp. 5812-5816 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Vol. 2022-May).

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abstract = "Transfer entropy can to a certain degree assess the direction in addition to the strength of the couplings within dynamic time series. The greater the transfer entropy, the greater the strength of the dependency between time series. In this work, we are interested in quantifying the effect that a given time series (e.g., an external stimuli) has upon the coupling strength between other time series. Towards that end, we define a directed dependency index based on the difference of two causally conditioned transfer entropies. We then provide a lower bound for the dependency index, and demonstrate on synthetic data that this lower bound can be efficiently computed.",

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author = "Baboukani, {Payam Shahsavari} and Sergios Theodoridis and Jan {\O}stergaard",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE; 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 ; Conference date: 23-05-2022 Through 27-05-2022",

year = "2022",

doi = "10.1109/ICASSP43922.2022.9747254",

language = "English",

series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

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Baboukani, PS, Theodoridis, S & Østergaard, J 2022, A Stimuli-Relevant Directed Dependency Index for Time Series. in 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings. IEEE Signal Processing Society, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2022-May, pp. 5812-5816, 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022, Virtual, Online, Singapore, 23/05/2022. https://doi.org/10.1109/ICASSP43922.2022.9747254

A Stimuli-Relevant Directed Dependency Index for Time Series. / Baboukani, Payam Shahsavari; Theodoridis, Sergios; Østergaard, Jan.
2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings. IEEE Signal Processing Society, 2022. p. 5812-5816 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Vol. 2022-May).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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AB - Transfer entropy can to a certain degree assess the direction in addition to the strength of the couplings within dynamic time series. The greater the transfer entropy, the greater the strength of the dependency between time series. In this work, we are interested in quantifying the effect that a given time series (e.g., an external stimuli) has upon the coupling strength between other time series. Towards that end, we define a directed dependency index based on the difference of two causally conditioned transfer entropies. We then provide a lower bound for the dependency index, and demonstrate on synthetic data that this lower bound can be efficiently computed.

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Baboukani PS, Theodoridis S, Østergaard J. A Stimuli-Relevant Directed Dependency Index for Time Series. In 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings. IEEE Signal Processing Society. 2022. p. 5812-5816. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Vol. 2022-May). doi: 10.1109/ICASSP43922.2022.9747254

A Stimuli-Relevant Directed Dependency Index for Time Series

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Keywords

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