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In these methods, the instantaneous frequency ridge extraction is one of the most important parts.
Analysis performed with 1 s segments: a instantaneous frequency ridge in wavelet map b instantaneous amplitude.
Lim et al.[48] present a local-feature-based quality metric which computes orientation certainty level (OCL), ridge frequency, ridge thickness, and ridge-to-valley thickness ratio.
Each time frequency ridge line represented all parameters of one oscillation (phase, frequency, amplitude, starting and ending times) as a function of time.
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As a result, an important time-frequency ridge with weak energy and intricate shape is successfully extracted by the proposed method, while two popular ridge estimation methods cannot well track the complete time-frequency ridge.
A time-frequency ridge,, represents continuous local energy maxima in the time-frequency domain.
We therefore chose to focus our paper on the time-frequency ridge extraction/reconstruction approach as the most suitable and promising method at our disposal.
The SPTFD matrix of the corresponding signal can be obtained by sampling each signal along its time-frequency ridge, and the corresponding noise subspace can be obtained by characteristic decomposition.
(2) With the estimated signal parameters to select points in the time-frequency domain, for signals of different frequency parameters, the points on respective time-frequency ridge were selected to construct their own SPTFD matrix.
(2) Using the estimated signal parameters to select points in the time-frequency domain, the different frequency parameters of the signal were selected on their respective time-frequency ridge points to construct their own spatial polarimetric time-frequency distribution matrix.
(2) Using the estimated signal parameters to select points in the time-frequency domain, for the different frequency parameters of the signal were selected on their respective time-frequency ridge points to construct their own SPTFD matrix.
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