Walters-Williams, Janett and Li, Yan (2010) Comparison of extended and unscented Kalman filters applied to EEG signals. In: 2010 IEEE/ICME International Conference on Complex Medical Engineering (CME 2010), 13-15 July 2010, Gold Coast, Australia.
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Official URL: http://dx.doi.org/10.1109/ICCME.2010.5558873
Identification Number or DOI: doi: 10.1109/ICCME.2010.5558873
For years the Extended Kalman Filter (EKF) has been the algorithm for non-linear systems due to its simplicity and suitability to real time implementations. Because of its shortfalls, however, the Unscented Kalman Filter (UKF) was introduced to be an algorithm which was more accurate. Since then researches have been conducted to investigate the suitability of both algorithms in different areas. This paper presents a comparison of the estimation quality for the two algorithms when applied to a real time system - Electroencephalography (EEG).
|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Additional Information:||© 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Uncontrolled Keywords:||extended Kalman filter; electroencephalography; EEG signals; electroencephalography; unscented Kalman filter; EEG|
|Fields of Research (FOR2008):||08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified|
10 Technology > 1004 Medical Biotechnology > 100402 Medical Biotechnology Diagnostics (incl. Biosensors)
08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080201 Analysis of Algorithms and Complexity
|Socio-Economic Objective (SEO2008):||E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences|
|Deposited On:||28 Feb 2011 17:14|
|Last Modified:||25 Feb 2013 09:46|
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