New methods of time series analysis for non-stationary EEG data: Eigenstructure decompositions of time varying autoregressions
Publication
, Journal Article
Krystal, AD; Prado, R; West, M
Published in: Clinical Neurophysiology
1999
Duke Scholars
Published In
Clinical Neurophysiology
Publication Date
1999
Volume
110
Start / End Page
1 / 10
Related Subject Headings
- Neurology & Neurosurgery
- 17 Psychology and Cognitive Sciences
- 11 Medical and Health Sciences
- 09 Engineering
Citation
APA
Chicago
ICMJE
MLA
NLM
Krystal, A. D., Prado, R., & West, M. (1999). New methods of time series analysis for non-stationary EEG data: Eigenstructure decompositions of time varying autoregressions. Clinical Neurophysiology, 110, 1–10.
Krystal, A. D., R. Prado, and M. West. “New methods of time series analysis for non-stationary EEG data: Eigenstructure decompositions of time varying autoregressions.” Clinical Neurophysiology 110 (1999): 1–10.
Krystal AD, Prado R, West M. New methods of time series analysis for non-stationary EEG data: Eigenstructure decompositions of time varying autoregressions. Clinical Neurophysiology. 1999;110:1–10.
Krystal, A. D., et al. “New methods of time series analysis for non-stationary EEG data: Eigenstructure decompositions of time varying autoregressions.” Clinical Neurophysiology, vol. 110, 1999, pp. 1–10.
Krystal AD, Prado R, West M. New methods of time series analysis for non-stationary EEG data: Eigenstructure decompositions of time varying autoregressions. Clinical Neurophysiology. 1999;110:1–10.
Published In
Clinical Neurophysiology
Publication Date
1999
Volume
110
Start / End Page
1 / 10
Related Subject Headings
- Neurology & Neurosurgery
- 17 Psychology and Cognitive Sciences
- 11 Medical and Health Sciences
- 09 Engineering