Authors:
Jindřich Liška
and
Eduard Janeček
Affiliation:
University of West Bohemia in Pilsen, Czech Republic
Keyword(s):
Instantaneous frequency, Kalman filter, time-frequency analysis, state estimation, Hilbert transform.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Signal Processing
;
Informatics in Control, Automation and Robotics
;
Signal Processing, Sensors, Systems Modeling and Control
;
Time and Frequency Response
;
Time Series and System Modeling
;
Time-Frequency Analysis
Abstract:
In this paper, a new method for obtaining a time-frequency representation of instantaneous frequency is introduced. A Kalman filter serves for dissociation of signal into modes with well defined instantaneous frequency. A second order resonator model is used as a model of signal components – ‘monocomponent functions’. Simultaneously, the Kalman filter estimates the time-varying signal components in a complex form. The initial parameters for Kalman filter are obtained from the estimation of the spectral density through the Burg’s algorithm by fitting an auto-regressive prediction model to the signal. To illustrate the performance of the proposed method, experimental results show the contribution of this method to improve the time-frequency resolution.