Adaptive spectral tracking for coherence estimation : the z-tracker
- Submitting institution
-
University of York
- Unit of assessment
- 12 - Engineering
- Output identifier
- 55024259
- Type
- D - Journal article
- DOI
-
10.1088/1741-2552/aaa3b4
- Title of journal
- Journal of Neural Engineering
- Article number
- 026004
- First page
- -
- Volume
- 15
- Issue
- 2
- ISSN
- 1741-2560
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
3
- Research group(s)
-
B - Intelligent Systems and Nano-Science
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A major challenge in studying the brain is detecting changes in functional interactions over time. Wavelets have become the accepted approach for time-dependent analyses. This paper presents a novel alternative using Kalman filtering to achieve a lower MSE and a x50 decrease in computation speed compared to complex wavelets. MATLAB software is freely available: http://www.neurospec.org/ as part of a software suite which has been downloaded over 5000 times.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -