DATA-ANSDNAMay 6, 2016

Wave-shape function analysis -- when cepstrum meets time-frequency analysis

arXiv:1605.01805v258 citations
Originality Incremental advance
AI Analysis

This work addresses signal processing challenges in fields like physiology, music, and biology, but appears incremental as it builds on existing cepstrum and time-frequency methods.

The authors tackled the problem of analyzing oscillatory signals with time-varying frequency, amplitude, and non-sinusoidal patterns by combining cepstrum and nonlinear time-frequency analysis, resulting in the de-shape synchrosqueezing transform algorithm that was validated on simulated and real-world signals.

We propose to combine cepstrum and nonlinear time-frequency (TF) analysis to study mutiple component oscillatory signals with time-varying frequency and amplitude and with time-varying non-sinusoidal oscillatory pattern. The concept of cepstrum is applied to eliminate the wave-shape function influence on the TF analysis, and we propose a new algorithm, named de-shape synchrosqueezing transform (de-shape SST). The mathematical model, adaptive non-harmonic model, is introduced and the de-shape SST algorithm is theoretically analyzed. In addition to simulated signals, several different physiological, musical and biological signals are analyzed to illustrate the proposed algorithm.

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