title: Multiharmonic tracking using sigma-point Kalman filter.
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.
authors.affiliation: Biomedical Signal Processing Laboratory, Portland State University, Portland, Oregon, USA. sunghan@pdx.edu
authors.forename: Sunghan
authors.initials: S
authors.lastname: Kim
authors.forename: Anindya S
authors.initials: AS
authors.lastname: Paul
authors.forename: Eric A
authors.initials: EA
authors.lastname: Wan
authors.forename: James
authors.initials: J
authors.lastname: McNames
mesh_terms: D000465:Algorithms; D001330:Electronic Data Processing; D004594:Electrophysiology / Q000379:methods; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D008962:Models, Theoretical; D016011:Normal Distribution; D012815:Signal Processing, Computer-Assisted; D012984:Software