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Optimal Time-Frequency analysis of the multiple time-translated locally stationary processes

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Author

Summary, in English

A previously proposed model for non-stationary signals is

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.

Department/s

Publishing year

2013

Language

English

Publication/Series

[Host publication title missing]

Document type

Conference paper

Publisher

IEEE - Institute of Electrical and Electronics Engineers Inc.

Topic

  • Probability Theory and Statistics

Keywords

  • 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

Research group

  • Statistical Signal Processing
  • Statistical Signal Processing Group