Title :
Multiharmonic tracking using sigma-point Kalman filter
Author :
Kim, Sunghan ; Paul, Anindya S. ; Wan, Eric A. ; McNames, James
Author_Institution :
Biomedical Signal Processing Laboratory, Portland State University, Portland, Oregon, U.S.A.
Abstract :
Several groups have proposed the state-space approach to track time-varying frequencies ofmulti-harmonic quasi-periodic signals contaminated with white Gaussian noise. We compared the extended Kalman filter (EKF) and sigma-point Kalman filter (SPKF) algorithms on this problem. On average, the SPKF outperformed the EKF and more accurately tracked the instantaneous frequency over a wide range of signal-to-noise (SNR) ratios.
Keywords :
Biomedical engineering; Biomedical signal processing; Frequency estimation; Hidden Markov models; Integral equations; Laboratories; Nonlinear filters; Power harmonic filters; Signal sampling; State-space methods; Extended Kalman filter; Sigma-Point Kalman filter; instantaneous frequency (IF); local minima issue; normalized frequency mean-square-error (NFMSE); Algorithms; Automatic Data Processing; Electrophysiology; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Models, Biological; Models, Statistical; Models, Theoretical; Normal Distribution; Signal Processing, Computer-Assisted; Software;
Conference_Titel :
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-1814-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2008.4649746
