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Based on the time and frequency modulation feature of dolphin whistles, a series of segmented chirp rate modulated signals are designed to mimic the dolphin whistles by sound characteristics.
Moreover, FAWT is effective in revealing the amplitude modulation feature of the periodic fault impulses that occur in some damaged rotating components.
Based on this time frequency analysis method, and considering the modulation feature of rolling bearing vibrations, we propose joint time-varying amplitude and frequency demodulated spectra to reveal the time-varying fault characteristic frequency.
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Algorithms based on some time-frequency distributions such as the ambiguity function (AF) [15], Zhao Altas and Marks (ZAM) representations [16], the Rihacek distribution and the Hough transform [17], were also applied to extract modulation features for five kinds of radar pulses.
To fully explore the relevance of the modulation feature space in capturing informative characteristics of musical timbre, we use the model with the chosen solo parsing parameters (for uniform windowing and harmonicity-parsing) to test classification accuracy in a matched and cross-domain setting.
Synthesised speech based on manipulations of these local amplitude modulation features was used to explore the basis of intelligibility.
Unlike the conventional automatic modulation classification methods which extract modulation features based on a list of known patterns, this proposed method classifies modulations by the existence of basic modulation components including continuous frequency modulations, discrete frequency codes and discrete phase codes in an autonomous way.
In the next section, we will therefore focus on modulation features that address the temporal structure of speech.
The solution of this constrained optimization problem can lead to a new system of multi-carrier modulation featuring an optimal performance.
The samples of pulse will be processed to extract some modulation features.
It concludes by stating that understanding the mechanisms underlying gain modulation is important because gain modulation is a prominent feature of neural activity recorded in behaving animals.
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