TY - GEN
T1 - A New Approach to Signal Processing of Spatiotemporal Data
AU - Slawinska, Joanna
AU - Ourmazd, Abbas
AU - Giannakis, Dimitrios
N1 - Funding Information:
This research was supported by NSF EAGER grant 1551489, NSF grant DMS-1723175, ONR YIP grant N00014-16-1-2649, and DARPA grant HR0011-16-C-0116.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/29
Y1 - 2018/8/29
N2 - We present a method combining ideas from the theory of operator-valued kernels with delay-coordinate embedding techniques in dynamical systems capable of identifying spatiotemporal patterns, without prior knowledge of the state space or the dynamical laws of the system generating the data. The approach is particularly powerful for systems in which characteristic patterns cannot be readily decomposed into temporal and spatial coordinates. Using simulated and observed sea-surface temperature data, we show our approach reveals coherent patterns of intermittent character with significantly higher skill than conventional analytical methods based on decomposing signals into separable spatial and temporal patterns.
AB - We present a method combining ideas from the theory of operator-valued kernels with delay-coordinate embedding techniques in dynamical systems capable of identifying spatiotemporal patterns, without prior knowledge of the state space or the dynamical laws of the system generating the data. The approach is particularly powerful for systems in which characteristic patterns cannot be readily decomposed into temporal and spatial coordinates. Using simulated and observed sea-surface temperature data, we show our approach reveals coherent patterns of intermittent character with significantly higher skill than conventional analytical methods based on decomposing signals into separable spatial and temporal patterns.
KW - Signal processing
KW - dynamical systems
KW - kernel methods
KW - multivariate time series
KW - spatiotemporal patterns
KW - vector-valued functions
UR - http://www.scopus.com/inward/record.url?scp=85053829110&partnerID=8YFLogxK
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U2 - 10.1109/SSP.2018.8450704
DO - 10.1109/SSP.2018.8450704
M3 - Conference contribution
AN - SCOPUS:85053829110
SN - 9781538615706
T3 - 2018 IEEE Statistical Signal Processing Workshop, SSP 2018
SP - 453
EP - 457
BT - 2018 IEEE Statistical Signal Processing Workshop, SSP 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE Statistical Signal Processing Workshop, SSP 2018
Y2 - 10 June 2018 through 13 June 2018
ER -