Optimal Time-Frequency analysis of the multiple time-translated locally stationary processes
Författare
Summary, in English
extended in this contribution. The model consists of mul-
tiple time-translated locally stationary processes. The opti-
mal Ambiguity kernel for the process in mean-square-error
sense is computed analytically and is used to estimate the
time-frequency distribution. The performance of the kernel
is compared with other commonly used kernels. Finally the
model is applied to electrical signals from the brain (EEG)
measured during a concentration task.
Avdelning/ar
- Matematisk statistik
- Statistical Signal Processing Group
- eSSENCE: The e-Science Collaboration
Publiceringsår
2013
Språk
Engelska
Publikation/Tidskrift/Serie
[Host publication title missing]
Dokumenttyp
Konferensbidrag
Förlag
IEEE - Institute of Electrical and Electronics Engineers Inc.
Ämne
- Probability Theory and Statistics
Nyckelord
- Time frequency analysis
- Locally stationary process
- Optimal Ambiguity kernel
- EEG.
Conference name
21st European Signal Processing Conference (EUSIPCO 2013)
Conference date
2013-09-09 - 2013-09-13
Conference place
Marrakech, Morocco
Status
Published
Forskningsgrupp
- Statistical Signal Processing
- Statistical Signal Processing Group